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Frances Shepherd
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YI02 - Clinical Trials (ID 108)
- Event: WCLC 2019
- Type: Young Investigator Session
- Track: Young Investigators
- Presentations: 5
- Now Available
- Moderators:Laura Mezquita, Frances Shepherd
- Coordinates: 9/07/2019, 09:00 - 10:30, Dublin (1997)
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YI02.01 - Academic Versus Industrial Clinical Trials (Now Available) (ID 3696)
09:00 - 10:30 | Presenting Author(s): Tony Mok
- Abstract
- Presentation
Abstract not provided
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YI02.02 - Basket and Umbrella Trial Designs in Oncology (Now Available) (ID 3697)
09:00 - 10:30 | Presenting Author(s): Jessica Menis
- Abstract
- Presentation
Abstract
Cancer treatment has made gigantic improvements in patients’ prognosis in multiple cancer types, by virtue of major steps forward in the concept of personalized medicine. This involves scientific progress in tumour biology, genomics technology, computational analysis and drug discovery that has propelled advances in both translational and clinical cancer research.
In particular, rapid development, decreased cost, and increased availability of next-generation genomic sequencing and other methods for both molecular and, more recently, immunological tumor classification have changed the paradigm for understanding and treating cancer.
Until recently, drug development has been conducted separately for different histological tumor types since the histological type was the primary known determinant of drug efficacy. However, this histology focus has been integrated by new knowledge on genomic alterations and immunological profile. Therefore, clinical trials have been evolving in parallel, from the traditional two-arm comparison of an experimental treatment vs. a control, to accelerate identification of promising therapies, to increase throughput and to allow for the increasing use of molecular and immunological classification of patients into smaller sub-groups.
Also cost-efficiency need to be considered: classical phase I, II and III models for drug development require large resources, limiting the number of experimental agents that can be tested and making the evaluation of targeted agents inefficient.
On the other hand, methodology and quality assurance need to be preserved since the validation of biomarkers is generally affected by several challenges, such as the multitude of assessment methods (i.e. immunohistochemistry, fluorescence in situ hybridisation, next-generation sequencing, etc.), reliability in terms of sensitivity and specificity, reproducibility of the test, feasibility of obtaining an adequate and representative tumour sample and, finally, the overall related costs.
All these considerations, added to the strong collaboration with the regulatory agencies, approving novel agents based on data obtained from phase 1/2 trials, have led to an evolution in the design of early-stage clinical trials.
The enrichment design can require many fewer patients, i.e. only those patients hypothesized to benefit, to be randomized relative to the “all comers” randomized design. The choice between an unselected versus enriched design should always be made also based on the existing level of evidence for the predictive biomarker.
Two main enrichment strategies can be used to avoid over-treatment and save valuable resources, by matching the right drug to the right subgroup of patients. They can be defined as: basket trials and umbrella trials.
Basket trials allow patients with multiple diseases and one or more target to be enrolled in cohorts or groups in one trial (the basket). They are often viewed as parallel phase II trials within the same entity, designed on the basis of a common denominator. Researchers are therefore allowed to separately analyse the patients’ responses as each tumour type can be put in one cohort, and assess the impact of the drug on all of the patients as one group. If one group shows a good response, this group will be expanded to immediately assess whether others could benefit from the new therapy. If another group does not show evidence of effectiveness, this group may be closed and the other cohort can continue the recruitment. Basket trials can be further sub-classified in three groups: basket trials on one drug in several tumour types (1), basket trials on one drug for one molecular alteration in several tumour types (2), and basket trials on one drug in several molecular alterations in several tumour types.
Umbrella trials are built on a centrally performed molecular portrait and molecularly selected cohorts with matched drugs, and can include patients’ randomisation and strategy validation. In the umbrella design, a separate enrichment trial is conducted for each bio- marker stratum. The enrichment design for a given stratum uses as the test regimen a drug expected to be active for the alteration defining that stratum.
Beyond new designs, new end-points and new evaluation techniques are also warranted to finally achieve methodology and clinical improvements, in particular within immunotherapy trials.
As clinicians continuously learn from their patients, applying knowledge gained from one set of patients to their forthcoming patients, in adaptive designs, modifications of some aspects of the trial can be prospectively planned so that changes (‘‘adaptations’’) may take place while the study is ongoing (for example: a treatment arm or a subgroup of patients could be dropped; the trial size could be increased, etc). Planning for such types of studies would allow to overcome the challenge related to the limited available information in the literature describing the targeted sub-populations.
Alongside the growing complexity of these clinical trials, new frameworks for stronger and faster collaboration between all stakeholders in drug development, including academic institutions and frameworks, clinicians, pharma companies and regulatory agencies, has to be further encouraged.
In the current era, the main goal should be to identify large and meaningful differences in small, molecularly and immunologically selected groups of patients and to develop rapidly new compounds. Basket and umbrella trials respond to the need of ‘‘trials designed to learn’’, that can evolve into ‘‘trials designed to conclude’’.
Menis J, Hasan B, Besse B. New clinical research strategies in thoracic oncology: clinical trial design, adaptive, basket and umbrella trials, new end-points and new evaluations of response. Eur Respir Rev 2014; 23: 367–78
Simon R. Critical Review of Umbrella, Basket, and Platform Designs for OncologyClinical Trials. Clin Pharmacol Ther. 2017; 102(6):934-41
Renfro LA, Sargent DJ. Statistical controversies in clinical research: basket trials, umbrella trials, and other master protocols: a review and examples. Ann Oncol. 2017;28(1):34-43
Garralda E, Dienstmann R, Piris-Giménez A, Braña I, Rodon J, Tabernero J. New clinical trial designs in the era of precision medicine. Mol Oncol. 2019;13(3):549-57
Renfro LA, Mandrekar SJ. Definitions and statistical properties of master protocols for personalized medicine in oncology. J Biopharm Stat. 2018;28(2):217-228
Rashdan S, Gerber DE. Going into BATTLE: umbrella and basket clinical trials to accelerate the study of biomarker-based therapies. Ann Transl Med. 2016;4(24):529
Morrell L, Hordern J, Brown L, et al. Mind the gap? The platform trial as a working environment. Trials. 2019; 20(1):297
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YI02.03 - Statistical Pitfalls in Clinical Trial Design (Now Available) (ID 3698)
09:00 - 10:30 | Presenting Author(s): Urania Dafni
- Abstract
- Presentation
Abstract
This topic will be discussed in the context of the following principles that clinical trials should adhere to.
A clinical trial is an experiment testing medical treatments on human subjects.
The process of evaluating medical treatment in humans starts with a Phase I clinical trial, followed by a Phase II and a Phase III trial towards regulatory approval.
Phase III
Phase III clinical trials are the gold standard for the evaluation of therapeutic interventions’ efficacy. The goals of a Phase III clinical trial include minimization of random error, elimination of systematic error (bias) and ensuring the generalizability of study results. The clinical trial design is the methodology for achieving these goals.
Randomization, always present in phase III trials, provides a treatment assignment that is independent of outcome and patient/disease features, thus balancing treatment groups on known and unknown factors associated with outcome. Further, the intention-to-treat (ITT) analysis approach is the gold standard for all phase III randomized, controlled clinical trials. It analyzes all patients in the treatment groups as randomized without regard to treatment actually received. The systematic error (Bias), which is any effect rendering the observed results not representative of the treatment effect, is addressed through randomization and corresponding ITT analysis. Minimization of random error is addressed through the use of adequately large sample size.
Phase II
Phase II clinical trials can be either randomized (screening, selection, randomized discontinuation designs) or non-randomized. The latter may be seriously misleading since the impact of prognostic factors is usually far larger than that of treatment, while known prognostic factors may explain little variance.
Randomized phase II trials allow control of selection bias and simultaneous testing of several new treatments, combinations, doses etc. They are preferable than non-randomized trials (some degree of control is better than none!) but they could be misleading due to the small sample sizes. They cannot replace phase III trials. In Phase II trials, the objective is to select active drugs for further testing and document toxicity, but not to provide definite estimate of new drugs’ efficacy, wh8ch is achieved only though a well-powered Phase III clinical trial.
Hypothesis Testing
In any experiment, two hypotheses covering all possible outcomes are pitted against each other. Only one of them can be true. The alternative hypothesis is the statement we would like to prove, and the null hypothesis, the statement we would like to reject. The only possible conclusions in hypothesis testing are: 1. Reject the Null Hypothesis, and thus prove the desired alternative hypothesis (positive trial), or 2. Not able to reject the null hypothesis (negative trial).
Any trial needs to be designed in such a way that it is known a-priori what the errors relative with each of the two possible conclusions will be. Rejecting the null wrongly (false positive result), is subject to Type-I error (alpha), or significance level, while not rejecting the null hypothesis wrongly (false negative result), is subject to Type-II error (beta). The sample size of the trial is decided at the design stage to guarantee that these two errors remain below pre-defined bounds. These bounds are usually 5% for Type-I error, and 20% for type II error.
One more important design characteristic is power, which is equal to (1-beta) and it is the probability of correctly rejecting the null hypothesis (values usually set above 80%).
Superiority vs Equivalence/Non-inferiority
Clear distinction should be made between superiority and equivalence/non-inferiority Phase III trials, with each testing a different type of null hypothesis. In a superiority trial we aim to reject a null hypothesis of “no effect” or “no difference”, while in an equivalence trial we aim to reject a null hypothesis of “different effect”.
More particularly, in a superiority trial we aim to demonstrate the superiority of a new therapy compared to an established therapy or placebo. In this case, the determination of the sample size takes into account the clinical significance (by how much the new therapy should be better than the established one), the power and the significance level of the test, as well as the magnitude of the variation of the corresponding measure of interest.
In equivalence trials, the objective is to demonstrate that a new treatment is equivalent to a standard therapy with regards to a specific clinical end point, while it has an intrinsic benefit for other clinical end points, while in non-inferiority trials, to evaluate whether the new treatment is not inferior to or as effective as the standard therapy for a particular end point. In this case, a tolerance and a non-inferiority margin must be predefined, along with the power and the significance level of the test.
Failure to reject the Null hypothesis should not be confused with acceptance of the Null hypothesis.
Subgroup Analysis
Another issue that should be taken into account in the design of a trial is subgroup analysis, involving multiplicity issues. It is common practice to perform multiple subgroup analyses, but the probability of a false positive finding (type-I error) increases as the number of subgroup analyses increases (curse of multiplicity).
Prognostic vs Predictive Marker
The correlation between a biomarker and a true clinical endpoint corresponds to a prognostic marker, but not to a predictive one. It is the statistically significant difference in treatment effect between the levels of the biomarker (treatment by group interaction), that characterizes a predictive biomarker.
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YI02.04 - Bioinformatics: The Basics (Now Available) (ID 3699)
09:00 - 10:30 | Presenting Author(s): Yu Shyr
- Abstract
- Presentation
Abstract
For physicians, advanced data science methods such as artificial intelligence (AI), machine learning and novel statistical methods are no longer just a headline in the news. Use of advanced data science methods are gaining acceptance in the field of medicine, as researchers push the limits of rapidly progressing technologies to assist in delivering excellence in health care.
With the growth in use of advanced data science methods, however, we must bear in mind the limitations of these technologies. AI—specifically, machine learning (ML) of the deep-learning type—is only as good as the training dataset from which the algorithm learns. Deep learning in the clinical setting is most highly developed for image recognition; a training dataset for this purpose consists of a large number of case and control images. The algorithm then uses these images to teach itself how to differentiate, for example, malignant lesions from benign tumors or normal tissue. If the training dataset consists only of unambiguous cases and controls—rather than representing real-world variation and ambiguity—the algorithm will fail to function as desired with real-world patients. Thus, well-considered experimental design remains essential to realize the promise of deep learning.
This talk will provide an overview of the state of the art in AI, machine learning, novel statistical methods, and deep learning algorithm for clinical application, including examples from the research literature as well as FDA-approved devices that use advanced data science methods. We will then address the pitfalls of deep learning, including the need for clear and rigorous standards for regulatory approval of devices and software. We close with thoughts on the future of advanced data science methods in medicine.
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YI02.05 - Principles to Get Your Paper Published (Now Available) (ID 3700)
09:00 - 10:30 | Presenting Author(s): Alex A Adjei
- Abstract
- Presentation
Abstract
How to get your Manuscript Published
Alex A. Adjei, MD;PhD
Mayo Clinic, Rochester, MN, USA
Scientific publication is the backbone of academic research. Findings by investigators need to be disseminated to the community so that results can influence human health and well-being as well lay groundwork for future research.
In spite of the central role of publishing in academic life described above, there are very few formal courses or seminars teaching academics, particularly physician scientists on how to publish their work. The table below outlines reasons for rejection of manuscripts, coming out of a survey of a number of journal editors
Using information from this survey as a starting point, we will discuss the “fatal flaws” that lead to outright rejection of manuscripts, and outline strategies on how to write a manuscript of high impact, which is likely to be accepted for publication.
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Author of
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ES14 - What First Line in Oncogene Addicted NSCLC (ID 17)
- Event: WCLC 2019
- Type: Educational Session
- Track: Targeted Therapy
- Presentations: 1
- Now Available
- Moderators:Dolores Isla, Jessica Menis
- Coordinates: 9/08/2019, 15:15 - 16:45, Vancouver (2003)
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ES14.03 - First Line in ROS1 Translocated Patients (Now Available) (ID 3232)
15:15 - 16:45 | Presenting Author(s): Frances Shepherd
- Abstract
- Presentation
Abstract not provided
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MA18 - Advances in Diagnosis of Common Types of NSCLC (ID 145)
- Event: WCLC 2019
- Type: Mini Oral Session
- Track: Pathology
- Presentations: 1
- Now Available
- Moderators:Yuko Minami, Mary Beth Beasley
- Coordinates: 9/10/2019, 11:30 - 13:00, Tokyo (1982)
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MA18.07 - Identification of Neuroendocrine Transformation in Anaplastic Lymphoma Kinase Rearranged (ALK+) Tumors After Tyrosine Kinase Inhibitors (Now Available) (ID 1137)
11:30 - 13:00 | Author(s): Frances Shepherd
- Abstract
- Presentation
Background
Acquired resistance after ALK tyrosine kinase inhibitors treatment has multiple known mechanisms: new mutations or gene amplifications, bypass signaling and rarely neuroendocrine histological transformation. Here we describe results of a program utilizing routine biopsy post-progression in ALK+ patients for clinical and research purposes.
Method
Since 2014, ALK+ lung cancer patients treated at the Princess Margaret Cancer Centre have undergone routine biopsies at disease progression time points upon failure of an ALK-tyrosine kinase inhibitor (TKI) for both clinical purposes and research purposes, in particular to obtain tissue for primary derived xenograft (PDX) engraftment.
Result
All 9/9 patients consented for research sampling during clinical biopsy procedures (median 2 extra cores/passes); 2 patients were biopsied more than once; 3 PDX models from 2 patients have engrafted; 3 additional models are too early to assess engraftment. Engraftment occurred in patients with clinically aggressive tumors and poor survival outcomes. In this process, we identified 2 patients with neuroendocrine transformation post-second generation ALK TKI: (a) a 59 yo Asian female, never smoker, diagnosed six years prior with metastatic disease, heavily pretreated with crizotinib (12 months), pemetrexed (16 months), ceritinib (25 months), alectinib (6 months) and brigatinib (3 months); post-alectinib biopsy showed no transformation, while post-brigatinib liver biopsy demonstrated transformation to large cell neuroendocrine carcinoma; (b) a 75 yo Caucasian female, never smoker, diagnosed eight months prior and started on alectinib with a partial response, progressed in a single site; endobronchial biopsy demonstrated high grade neuroendocrine transformation. Both biopsies were positive for neuroendocrine markers (chromogranin and synaptophysin), TTF-1 and diffusely co-expressed ALK on immunohistochemistry. Assessment of PDX engraftment of these models is ongoing.
Conclusion
Routine combined clinical and research biopsy of ALK+ patients at time of TKI failure helped to identify these recent cases of neuroendocrine transformation as a possible mode of resistance and provide tissue for model development. This is the first time that ALK+ transformation to large cell neuroendocrine carcinoma is reported in the literature. (PP, AFF, SNMF, LN contributed equally).
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OA13 - Ideal Approach to Lung Resection and Novel Perioperative Therapy (ID 146)
- Event: WCLC 2019
- Type: Oral Session
- Track: Treatment of Early Stage/Localized Disease
- Presentations: 1
- Now Available
- Moderators:Tomasz Grodzki, Kenji Suzuki
- Coordinates: 9/10/2019, 11:30 - 13:00, Toronto (1985)
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OA13.01 - SPECS2 Lung Cancer Consortium Prospective Multicenter Validation of Prognostic Signature for Early Stage Squamous Lung Cancer (Now Available) (ID 2723)
11:30 - 13:00 | Author(s): Frances Shepherd
- Abstract
- Presentation
Background
Squamous Lung Cancer (SC) which constitutes 30% of all non-small cell lung cancers (NSCLC) has few targeted therapy options for advanced disease. Surgery for early SC is the best treatment strategy; however, even patients who undergo surgery for stage IA or IB disease are still at a substantial risk for recurrence and death. Adjuvant therapy is not currently indicated for stage I SC smaller than 4 cm. Prior reports suggest gene expression-based signatures that may predict recurrence in patients with stage I SC, but none has been validated or is in clinical use. The SPECS2 Lung Cancer Consortium was assembled to compare and attempt to validate previously published prognostic signature(s) according to the guidelines proposed by Subramanian and Simon (J Natl Cancer Inst 2010; 7:327).
Method
The multi-institutional team assembled 249 frozen SC samples representing six participating institutions (cohort 1). These samples were fully annotated in a redcap database hosted by the independent statistical core. Cohort 2 was assembled utilizing 234 frozen SC samples from a prospective multi-institutional NCTN lung biobanking protocol (NCT00899782). RNA was extracted and profiled with U133A microarrays (Affymetrix) in independent core facilities. The data was transferred directly to the SPECS2 Lung statistical core in collaboration with the Alliance Statistical core and the performance of 6 most promising candidate signatures was evaluated relative to a base model that included only age, gender and AJCC stage (editions 6, 7, 8).
Result
Analysis of Cohort 1 demonstrated that only one signature (Raponi et al, Cancer Res 2006; 66:7466) significantly enhanced prognosis relative to the base model, independent of AJCC edition. This was also observed in Cohort 2, where Uno’s C index associated with AJCC 8th edition stage, sex and age (0.561; 0.468-0.654) was significantly (p <0.05) increased when the prognostic signature was added to the model (0.683; 0.611-0.755).
Conclusion
The SPECS2 Lung Cancer Consortium was successful in validating a previously published prognostic molecular signature for early stage SC using rigorous experimental design. To our knowledge, this is the first unbiased validation of a lung cancer prognostic signature using multi-institutional prospective specimens. These results support a clinical trial designed to evaluate the potential role of adjuvant therapy in completely resected early stage SC.
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P1.01 - Advanced NSCLC (ID 158)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Advanced NSCLC
- Presentations: 2
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.01-30 - Non-Small Cell Lung Cancer (NSCLC) Next Generation Sequencing (NGS): Integrating Genomic Sequencing into a Publicly Funded Health Care Model (Now Available) (ID 2588)
09:45 - 18:00 | Author(s): Frances Shepherd
- Abstract
Background
Standard of care (SOC) molecular diagnostics for stage IV NSCLC patients in Ontario, Canada includes publicly reimbursed EGFR/ALK, and BRAF/ ROS-1 testing in selected cases. Other genomic alterations are not tested routinely at all institutions; however, enhanced molecular testing may broaden treatment options for patients by identifying actionable targets. This study evaluated costs, identified actionable targets, and determined clinical trial eligibility as a result of using the Oncomine Comprehensive Assay v3 (OCA v3, ThermoFisher) NGS in stage IV NSCLC patients at a single institution.
Method
This prospective study of stage IV NSCLC out-patients at Princess Margaret Cancer Centre (Toronto) began in February 2018 and recruitment is ongoing (NCT03558165). NSCLC patients without EGFR/ALK/KRAS/BRAF alteration (unless failure of prior targeted therapy and tissue rebiopsy), had diagnostic samples tested by OCAv3 (ThermoFisher; 161 genes: hotspots, fusions, and copy number variations). Primary endpoints were identification of incremental actionable targets and clinical trial opportunities as a result of broader OCAv3 testing. Secondary endpoints include feasibility and cost from the Canadian public healthcare perspective.
Result
From Feb 2018- Jan 2019 65 patients were enrolled [62% (N=40) completed/ 21% (N=14) screen fail/ 17% (N=11) pending], median age of completed cohort was 65, 60% (N=24) female, never/light smokers 68% (N=27), Asian 38% (N=15), previously treated 33% (N=13). Actionable targets beyond SOC were identified in 33% (N=13): ERBB2 (N=8), BRAFV600 (N=3), NRG fusion (N=1), MET exon 14 (N=1). Failure of NGS was secondary to insufficient tissue. 91% (N=10) of screen failures was secondary to tissue exhaustion from prior sequential SOC molecular testing. New clinical trial options were identified in 70% as a result of OCA v3 testing. Incremental costs per case beyond EGFR/ALK are estimated at $540 CAD. If ROS-1 and BRAF testing were publicly reimbursed at current rates, the incremental profiling cost with OCAv3 would be $90 CAD per case.
Conclusion
The OCAv3 consolidates genomic testing, identifies additional actionable targets, and substantially increases clinical trial eligibility for patients at a small incremental cost. Sample failures are reflective of exhausted diagnostic tissue as a result of prior sequential genomic testing. The key barrier to implementation of NGS remains funding in the Canadian health care system.
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P1.01-70 - Dominant Circulating Myeloid Populations Are Associated with Poor Response in NSCLC Treated with 1st Line PD-1 Monotherapy (Now Available) (ID 2295)
09:45 - 18:00 | Author(s): Frances Shepherd
- Abstract
Background
Immune subpopulations within the tumor microenvironment (TME) play a central role in determining response to checkpoint inhibitors. Myeloid derived suppressor cells (MDSC), a heterogeneous population of immature myeloid cells, have a predominantly immunosuppressive role by stimulating T regulatory cells. We hypothesize that elevated myeloid-to-lymphocyte measures in the peripheral blood predict for greater numbers of myeloid derived suppressor cells in the TME and worse outcomes.
Method
We identified all advanced NSCLC patients treated with immunotherapy between 2010-2019 at the Princess Margaret Cancer Center. Patients who received first line monotherapy with a PD-1 inhibitor were reviewed for clinical information including age, sex, histology, stage, smoking status, ethnicity, PD-L1 expression and tumor genotype. Myeloid cells lines analyzed included neutrophils, monocytes and platelets, expressed as ratios to peripheral lymphocytes. Multivariate analyses were conducted using the cox and logistic regression models to adjust for confounders.
Result
We identified 75 patients who were eligible for analysis. Disproportionate increases in the different myeloid cell types were highly correlated with each other (all Pearson’s rho>0.8) and the neutrophil to lymphocyte ratio (NLR) was selected as representative. A high NLR (>5) was associated with shorter time-to-treatment-failure (median TTF 9.7 vs 29.4 months) that remained significant after adjusting for confounders including PD-L1 and presence of liver metastases (p=0.004). High NLR was also an independent predictor of poor OS (median 11.3 vs 56.8 months, HR 3.02, p=0.04). Although NLR was not predictive of radiographic response, there was a trend to association with a rapidly progressive phenotype defined by primary progressive disease and a duration of therapy ≤2 months (p=0.06). Other predictive factors included the presence of liver metastases, which was associated with a worse OS (HR3.37 p=0.05) but not TTF (p=0.14). An association was also seen between NLR and liver metastases (mean NLR 6.6 vs 25.2 in the absence and presence of liver metastases respectively, p<0.001).
Conclusion
A disproportionate increase in peripheral immune myeloid populations may represent a systemic, myeloid-driven, immunosuppressive state that is significantly associated with primary refractory disease, rapid progression, and poor survival. A subset of about 50 patients with biobanked tissue are presently being analyzed using multiplex immunofluorescence to assess for MDSCs in the TME to correlate with peripheral blood findings.
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P1.10 - Prevention and Tobacco Control (ID 175)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Prevention and Tobacco Control
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.10-05 - Tobacco Retail Availability and Tobacco Cessation Among Lung Cancer Survivors (ID 1089)
09:45 - 18:00 | Author(s): Frances Shepherd
- Abstract
Background
Continued smoking after a lung cancer diagnosis is associated with poorer outcomes. Tobacco retail availability is negatively associated with cessation in non-cancer patients but this has not been explored in cancer survivors. We evaluated the impact of tobacco retail availability on tobacco cessation in lung cancer survivors.
Method
Lung cancer survivors from Princess Margaret Cancer Centre (Toronto, Canada) completed questionnaires at diagnosis and follow-up evaluating changes in tobacco use with a median of 26 months apart. Validated tobacco retail location data were obtained from Ministry of Health and patient home addresses were geocoded using ArcGIS 10.6.1, which calculated walking time/distance to nearest vendor, and vendor density within 250 meters (m) and 500m from patient residences. Multivariable logistic regression and Cox proportional hazard models evaluated the impact of vendor availability on cessation and time to quitting after diagnosis respectively, adjusting for significant clinico-demographic and tobacco covariates.
Result
242/721 lung cancer survivors smoked at diagnosis; subsequent overall quit rate after diagnosis was 66%. Mean distance and walking time to a vendor was 0.8 km (range 0-13) and 10 min (range 0-157). On average, there was one vendor (range 0-19) within 250m and five vendors (range 0-36) within 500m from pts; 40% and 64% of pts lived within 250m and 500m from at least one vendor respectively. Greater distance (aOR 1.28 per 1000m [95% CI 0.97-1.70] p = 0.08) and increased walking time (aOR 1.02 per minute [1.00-1.05] p = 0.08) to a tobacco vendor had a non-significant trend towards increased chances of quitting at one year. Living within 250m (aOR 0.43 [0.25-0.74] p = 0.003) or 500m (aOR 0.50 [0.28-0.88] p = 0.02) to at least one vendor reduced quitting at one year. Living near more vendors within 500m had a non-significant trend towards having an increasing dose effect on reducing cessation rates at one year (aOR 0.97 per vendor [0.94-1.00] p = 0.08). Living within 500m to a vendor reduced chance of quitting at any time (aHR 0.70 [0.50-1.00] p = 0.05).
Conclusion
Close proximity to tobacco retail outlets is associated with reduced cessation rates for lung cancer survivors. Reducing density of tobacco vendors is a cessation strategy that could positively impact lung cancer patient outcomes.
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P1.14 - Targeted Therapy (ID 182)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Targeted Therapy
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.14-07 - Genomic Profiling of Liquid Biopsies During 2nd/3rd Generation ALK Inhibitor Therapy to Identify Novel Mechanisms of Resistance (ID 804)
09:45 - 18:00 | Author(s): Frances Shepherd
- Abstract
Background
Second- and third-generation ALK inhibitors each have diverse mechanisms of resistance. Only a fraction of resistance is due to secondary mutations of the ALK gene. Altered bypass tracts are likely the case in some other instances. Genomic alterations of other genes and pathways may be a third mechanism of resistance. Repeat liquid biopsies during the course of patients’ treatments can provide a minimally invasive method for sampling cancer-specific genomic information that leads to improved treatment selection.
Method
In the Lung Cancer Clinic of the Princess Margaret Cancer Centre, serial plasma samples were collected from six lung cancer patients with ALK rearrangement at multiple serial clinic visits pre- and post- progression on next-generation ALK inhibitors. We focused on next generation agents, as there has been previous focus on crizotinib resistance mechanisms already. Cell-free DNA (cfDNA) was extracted (median: 50 ng; range: 20-2760 ng) and profiled using a next-generation sequencing (NGS) platform with Geneseeq Prime 425-gene panel at a mean coverage depth of 4747X (and a deduplicated mean coverage depth of 2160X).
Result
Somatic alterations from plasma cfDNA were detected in all six patients at various time points with three patients having detectable ALK alterations. Systemic progression (2/2 patients) correlated well with the ability of liquid biopsies to detect somatic mutations, while central nervous system (CNS)-predominant progression did not (4/4 patients). One patient, after disease progression on ceritinib, alectinib and brigatinib, exhibited variable allele fractions (AFs) of ALK G1202R mutation in cfDNA. The levels of G1202R decreased and ultimately became undetectable, corresponding to the patient’s clinical response to lorlatinib. In a patient who exhibited significant systemic progression, a massive increase in mutation AFs and many newly acquired mutations were detected in the cfDNA, including NOTCH1, DICER1, BRCA2, TP53, CDKN2A, ERBB3, and FAT1mutations. However, the increase in the number of co-mutations was not related to increases in the amount of extracted cfDNA.
Conclusion
Broad panel-based NGS of plasma cfDNA enabled noninvasive detection of systemic (but not CNS-predominant) progression during second and subsequent generation ALK inhibitor treatment, and can identify known and putative mechanisms of resistance for treatment decision-making.
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P2.03 - Biology (ID 162)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Biology
- Presentations: 2
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.03-11 - Impact of Ethnicity on Outcome in Never Smokers with EGFR and ALK Wildtype (EGFR/ALK-Wildtype) Lung Adenocarcinomas (ID 2035)
10:15 - 18:15 | Author(s): Frances Shepherd
- Abstract
Background
EGFR-mutations and ALK-rearrangements are frequent in lung adenocarcinoma (LUAD) samples from never smoker patients. Nevertheless, up to a quarter of all LUAD cases in never smokers are EGFR/ALK-wildtype: these patients have limited therapeutic options and few well-established clinical and molecular predictors of outcome. Our main objectives here were to investigate the prognostic impact of ethnicity in never smoker patients with EGFR/ALK-wildtype LUAD and seek for specific somatic events correlated to ethnical background in these patients.
Method
We included 85 samples from lifetime never-smoker patients with EGFR/ALK-wildtype LUAD collected from surgical resection with curative intent. Stages 1/2/3 were identified in 56 (66%)/15 (18%)/14 (16%) samples. A subset of those samples (n=46), with similar stage distribution, had snap-frozen tumor and paired-adjacent tissue available and were submitted to paired-end whole-exome sequencing. Fisher’s exact and Chi-squared tests were used to compare specific mutations between Asians vs non-Asians. Recurrence-free-survival (RFS) was calculated based on the Kaplan-Meier method; Cox modeling was used to generate hazard ratios (HR), adjusted for key clinical features.
Result
Most patients in the cohort were female (63/85, 74%); the median age was 68 years; median follow-up was 51 months. According to self-reports, 19/85 (22%) and 66/85 (78%) patients identified as Asians and non-Asians, respectively; no major clinical and pathologic differences were identified between these populations. Five-year recurrence free survival was significantly lower for Asians compared to non-Asians (50% vs. 78%, adjusted HR = 2.9; CI = 1.1-7.8, p=0.02), Figure 1. Among somatic events, in-frame deletions in CNPY3 (Toll-like receptor-specific co-chaperone for HSP90B1) were more frequent in Asians (30%) compared to non-Asians (18%). In contrast, DDX11 missense mutations (21% vs 0%; nucleic acid binding protein involved in genome stability), NOTCH2 multi-hits and frame-shift deletions (7% vs 1%), and KRAS missense mutations (7% vs 0%) were more frequently altered in non-Asians than in Asians.
Conclusion
In our cohort of never-smoker patients with EGFR/ALK-wildtype LUAD, Asian patients showed higher relapse rates than non-Asians. We identified differentially mutated genes by ethnicity that may partly account for these differences in outcome. (SNMF and AFF contributed equally)
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P2.03-37 - Genomic Landscape of EGFR/ALK Wild-Type Lung Adenocarcinomas in Never-Smokers and Importance of Epithelial-Mesenchymal-Transition (ID 1283)
10:15 - 18:15 | Author(s): Frances Shepherd
- Abstract
Background
The molecular landscape of EGFR/ALK wild-type Lung Adenocarcinomas in never-smokers is poorly understood. Never-smokers usually have low PD-L1 expression and low Tumor Mutation Burden, challenging treatment strategies when no known driver-mutations are found. To identify putative driver mutations, we compared whole exome sequencing (WES) results in the EGFR/ALK wild-type Lung Adenocarcinoma in the never smokers Toronto cohort with a corresponding EGFR/ALK wild-type Lung Adenocarcinoma group of smokers from TCGA.
Method
For never-smokers with resected EGFR/ALK wild-type Lung Adenocarcinomas, frozen tumor and paired-normal-lung were evaluated by WES at a mean coverage of 238x. The paired-end reads were aligned using BWA and were further processed using the standard GATK pipeline. Somatic mutations and indels were identified using MuTect and VarScan, respectively. We compared mutations from our cohort to the TCGA smokers who had EGFR/ALK wild-type Lung Adenocarcinomas from publicly available data (TCGA) to identify genes at least 10% more frequently mutated in never smokers compared to the TCGA cohort.
Result
In our cohort with 45 never-smoker patients, 80% were females; median age was 70y; 29% were Asians; Stage I/II/III+ were 71%/15%/13%; after a median follow-up of 69 months, 24% had recurred. Median non-synonymous Tumor Mutation Burden was 1.3mut/Mb in never-smokers. We identified 39 genes that were more frequently mutated in never-smokers vs smokers, including some known tumor suppressor genes. The most prevalent genes included ADAM21 missense mutations (21% vs 1%; adj p=0.003), NOTCH2 frame-shift deletions and multi-hit mutations (40% vs 17%; adj p=0.04), MST1 missense mutations and in-frame deletions (13% vs 0%; adj p=0.008), ZMIZ2 frame-shift insertions (13% vs 0%; adj p=0.008) and FOXD4 missense mutations (10% vs 0%; adj p=0.02). Many of these differentially mutated genes have been previously associated to epithelial-mesenchymal-transition signaling pathways. Conversely and as expected, KRAS, TP53, STK11 and KEAP1 were more frequently mutated in the TCGA smokers EGFR/ALK wild-type Lung Adenocarcinomas cohort.
Conclusion
We identified multiple genes, particularly involved in the epithelial-mesenchymal-transition signaling pathways that are over-represented in never-smokers with EGFR/ALK wild-type Lung Adenocarcinomas, when compared to smokers with EGFR/ALK wild-type Lung Adenocarcinomas. This is a novel finding with potential clinical importance. Validation studies, analyzing epithelial-mesenchymal-transition signaling activation pathways on the EGFR/ALK wild-type Lung Adenocarcinomas never smokers population are needed to best identify the actual role in carcinogenesis and metastasis, guiding future treatment strategies. (AFF and SNMF contributed equally).
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P2.14 - Targeted Therapy (ID 183)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Targeted Therapy
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.14-62 - Early, Subclinical SCLC Transformation in Patients with EGFR Mutant Lung Cancer Receiving Osimertinib, Detected Through Cell-Free DNA (ID 812)
10:15 - 18:15 | Author(s): Frances Shepherd
- Abstract
Background
Liquid biopsies provide a convenient approachfor serial sampling and real-time disease monitoring, leading to the early detection of treatment response, disease progression and drug-resistance. Here,we present genomic profiling of serial liquid biopsies from seven lung cancer patients with activatingEGFRmutations receiving osimertinib in clinical practice.
Method
At Princess Margaret Cancer Centre, in the Lung Cancer Outpatient Clinics, plasma samples were obtained from each patient at defined clinical visits (between ~1–5 months in-between visits). Cell-free DNA (cfDNA; with a median of 57 ng; range: 3.5 to 3806 ng) was extracted from plasma samples and profiled using targeted capture next-generation sequencing with the Geneseeq Prime 425-gene panel, at a mean coverage depth of 4892X (with a deduplicated mean coverage depth of 2108X).
Result
Systemic tumour burden correlated with the detection of genomic alterations in cfDNA: Four of four of the patients with low tumour burden, despite minor disease progression, exhibited minimal EGFR and co-mutation allele frequencies (AFs). Conversely, significant increases in systemic (but not central nervous system) tumour burden led to increases in driver and co-mutation AFs (two our of three patients). EGFR C797S mutation and inactivating mutations in RB1 and TP53 were detected in the cfDNA of one patient nearly four months prior to the development of small cell lung cancer (SCLC) transformation confirmed on tissue biopsy with distinct transformed and untransformed areas. Both of the specific RB1 and TP53 mutations found in cfDNA have been previously associated with SCLC. Subsequent combination cisplatin-etoposide chemoradiation resulted in temporary complete remission of the transformed SCLC, corresponding to loss of RB1 mutation detection by cfDNA testing.
Conclusion
Profiling of plasma cfDNA using hybrid capture deep sequencing of a large gene panel can detect early subclinical transformation of EGFR-mutated lung cancer into small cell lung cancer (i.e., neuroendocrine transformation), leading to earlier diagnosis and management of the transformed disease. Serial liquid biopsy profiling can also be used to monitor disease progression. However, detection sensitivity of tumour cfDNA largely depends on systemic tumour burden.
