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C. Dooms
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MINI 01 - Pathology (ID 93)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:W.A. Franklin, A.G. Nicholson
- Coordinates: 9/07/2015, 10:45 - 12:15, Mile High Ballroom 2c-3c
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MINI01.11 - Transcriptome Sequencing of Tumor vs. Surrounding Non-Malignant Lung Tissue in Non-Small Cell Lung Cancer (ID 1765)
11:45 - 11:50 | Author(s): C. Dooms
- Abstract
Background:
Both the response and the therapeutic ratio of targeted agents in NSCLC may depend on the expression of the target molecules in the tumor and the surrounding non-malignant lung tissue. We therefore performed transcriptome analysis and investigated correlations with histology, gender, age, CRP level and smoking status as well as evaluated the differential pathway expression in primary resected NSCLC and the surrounding non-malignant lung of the same patient.
Methods:
Transcriptome sequencing was performed on the primary tumor and distant lung tissue of the same patient from resection specimens of NSCLC patients. Differential gene expression between different conditions was identified using the statistical algorithms Cufflinks, EdgeR and DeSeq. Differential expression with P-values <0.05 after Benjamini-Hochberg correction was considered significant. Pathway analysis for overall tumor versus distant lung tissue was performed with the PANTHER gene classification platform using the Cufflinks, DeSeq and EdgeR differentially expressed gene sets as input.
Results:
Twenty-five patients were studied, 19 males and 6 females, with a median age of 69 years. Ten were current smokers, 14 former smokers (>4 weeks before surgery) and 1 non-smoker. Eleven patients had squamous cell carcinoma, 14 adenocarcinoma. A heat map with the results for the most commonly targeted genes in NSCLC is represented in figure 1. When compared to distant lung tissue, PD-L1 was downregulated in tumor tissue of adenocarcinoma and active smokers, but not in squamous cell carcinoma or ex-smokers. Internal control of tumor tissue of squamous vs. adenocarcinoma and ex-smokers vs. active smokers shows an important trend towards a higher expression of PD-L1 in squamous cell carcinoma and ex-smokers in both Cufflinks and EdgeR algorithms. Additional pathway analysis revealed 188 differentially regulated pathways. The most notable were downregulation of VEGF signaling, angiogenesis and B and T cell activation in tumor tissue when compared to distant lung tissue. Figure 1
Conclusion:
Our first results show a higher expression of PD-L1 in squamous tumors than in adenocarcinoma and a higher expression in tumors of ex-smokers than in those of active smokers. This may have consequences for the therapeutic ratio with anti-PD-L1 treatment. Downregulation of VEGFR-genes in tumor tissue was observed across almost all conditions. We will make this data more complete by adding methylation data as well as immunohistochemistry for protein localization.
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MINI 22 - New Technology (ID 134)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
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MINI22.06 - The Challenge of Molecular Testing for Clinical Trials in Advanced Non-Small Cell Lung Cancer Patients: Analysis of a Prospective Database (ID 1240)
17:15 - 17:20 | Author(s): C. Dooms
- Abstract
- Presentation
Background:
Molecular testing has become important in managing advanced non-small cell lung cancer (NSCLC), both in clinical practice, as well as in clinical trials. For the latter, tissue samples often have to be analysed in a central laboratory. We evaluated the turnaround time and possible delay in start of therapy in this process.
Methods:
We reviewed our prospective database on all molecular testing cases for clinical trial suitability in patients with advanced NSCLC between March 1, 2011 (start) and October 31, 2014. The following time points were considered: T1 (request for tissue sections from the pathology lab); T2 (receipt of sections and shipment); T3 (arrival of sections in central lab (CL)); T4 (receipt of biomarker result from CL).
Results:
251 patients were considered for biomarker-driven trials. Twenty-three cases did not have further analysis, as the request for central molecular testing was cancelled: insufficient tissue (n=11); exclusion criterion (n=10); patient refusal (n=2). Results for the remaining 228 patients were: failure of central biomarker analysis due to insufficient quantity of tissue (n=18), or quality of tissue (n=3, i.e. decalcification or poor fixation). Valuable results were obtained for 207 patients. In 91 of 228 (39.9%) samples sent, a biomarker of interest was documented. This led to 34 clinical trial inclusions. Other patients were no longer eligible due to loss of performance status (n=20), loss of contact (n=14), no trial slot available at the appropriate time (n=18), or exclusion criteria (n=5). The mean waiting time between signing informed consent (T1) and receiving results of the biomarker analysis (T4) was 25.1 calendar (SD 17.3) days (Table). The preparation of the unstained slides by the pathology lab took about 9.1 (SD 6.8) days, the time of the biomarker testing itself accounted for 12.8 (SD 7.3) days. For 18 of 228 (7.9%) patients, repeated sample shipments were needed because of insufficient tumor cells, their mean waiting time between informed consent and receiving the biomarker result was 62.2 (SD 38.4) days. Table: Waiting times (t) in molecular testing for 228 patients.Time interval Mean StDev Median Range Pathology lab (T2-T1) 9.1 6.8 7.0 1 - 70 Shipment (T3-T2) 1.8 1.6 1.0 0 - 17 Analysis (T4-T3) 12.8 7.3 12.0 2 - 58 Request to result (T4-T1) 25.1 17.3 22.0 7 - 184
Conclusion:
While molecular testing is important in many NSCLC trials, our results show that waiting times for central laboratory analysis can cause an important delay in treatment initiation, and even ineligibility for the trial(s) under consideration. Start of therapy based on properly validated local testing, with a posteriori central biomarker testing to guarantee the integrity of the trial, would be more rewarding for quite some patients.
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MS 19 - Global Nursing Issues in Lung Cancer (ID 37)
- Event: WCLC 2015
- Type: Mini Symposium
- Track: Nursing and Allied Professionals
- Presentations: 1
- Moderators:P. Hollen, B. Ivimey
- Coordinates: 9/08/2015, 14:15 - 15:45, 708+710+712
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MS19.01 - Nursing Challenges in Clinical Trials (ID 1931)
14:20 - 14:33 | Author(s): C. Dooms
- Abstract
- Presentation
Abstract:
Background: The model of clinical trials in lung cancer has evolved quite dramatically over the past years. Expanded phase I trials in biomarker-driven populations are a new paradigm of accelerated drug approval. Enrolling patients in these clinical trials creates several new challenges. Clinical Research Nurses (CRNs) play an important role in recruitment, actual drug delivery, and monitoring of this whole process. Methods: Identify the different barriers to recruitment that CRNs face with these clinical trials. Barriers to participation can be patient-related, physician-related or tissue-related. Review of literature was the basis for the patient- and physician-related barriers. To identify the tissue barriers, we studied our own database. We also present practical tips to overcome these barriers out of own expertise in the field. Results: Patients’ barriers to participate in clinical trials include individual characteristics, practical issues, and attitudes. The most common barriers are the individual characteristics: cultural background, health literacy, ethnicity, and age. Lack of knowledge, insurance coverage, extra appointments, reimbursement, and patient ineligibility are typical practical barriers. Attitudinal barriers are reluctance to randomisation, fear for side effects, and efficacy concerns (e.g. allocation to placebo) (1-3). To overcome these barriers the trial should be explained clearly. Patient should be supported in what may be a difficult decision and should not be pressured to do so. Dedicated CRNs may help with monitoring the recruitment process, providing additional information, and obtaining informed consent (1). The process of informed consent is the optimal time to define clearly the terms of the clinical trial, and to explain the sometimes difficult to understand medical and legal terms in the informed consent document. Optimally, this should lead to good understanding by the patient of the potential benefits and risks (4). Main physicians’ barriers are lack of time due to competing priorities, insufficient staff and training to meet the ever increasing procedures from competent authorities or institutional review boards and finance departments, worry about the impact on the doctor-patient relation, concern for patients, and lack of reward and recognition. Lack of time is considered a major barrier. Doctors experience time pressure from their usual clinical practice and management duties. Recruitment, the consent process, and the follow up of clinical trials on top of that demand a large piece of extra time (1;4;5). Lack of support staff, for example CRNs, can also account for poor recruitment. A stable clinical research team is likely to be advantageous. CRNs should not only have expert clinical and well developed critical thinking skills, but be well acquainted with the complex scientific, regulatory, and ethical aspects of clinical research (6). Well trained and experienced CRNs truly are “PI-extensions”. By monitoring the clinical activity to find possible candidates for trials, they support the physician with recruitment, and later on with the follow-up of included patients. Over the last years, we saw a major progress in the treatment of advanced non-small cell lung cancer, largely due to new targeted agents, monoclonal antibodies, and immunomodulatory agents. Both in clinical practice, as well as in clinical trials, the availability of tissue for biomarker analysis – in order to make the best choice for the patient – is crucial. Tissue availability is a new important barrier to clinical trials, as we noted from our own experience (7). Moreover, central lab confirmation of an already known biomarker, is often requested before the patient is allowed to start therapy, leading to sometimes important delays. In our respiratory oncology trial unit, we analysed of our molecular database regarding this barrier (7). The mean waiting time between signing informed consent and receiving results of the biomarker analysis from the central laboratory turned out to be 25 calendar days! While delivering a tissue sample for central confirmation of molecular testing is crucial in biomarker-driven NSCLC trials, the mandatory waiting of patients to start therapy is to be discussed. Waiting times for central laboratory analysis not only lead to an important delay in treatment initiation, but even ineligibility for the trial(s) under consideration. Start of therapy based on a properly validated local test, with a posteriori central biomarker testing to guarantee the integrity of the trial, would be more rewarding for quite some patients (8). Conclusion: Recruitment in lung cancer clinical trials is a complex and vulnerable process with different types of barriers. Identifying such barriers can help clinical trial staff to develop strategies to optimize participation and cooperation. Well-trained CRNs have a unique knowledge and set of skills that allows them to make a significant contribution to the clinical research team. CRNs should follow the rapid change in clinical trials closely, so that they can be a guide for patients in their clinical trial journey. Moreover, they have an important role in minimising the patient barriers, give support in physician barriers, and facilitating tissue barriers. References (1) Ross S, Grant A, Counsell C et al. Barriers to participation in randomised controlled trials: A systematic review. J Clin Epidemiol 1999;52:1143-1156. (2) Manne S, Kashy D, Albrecht T et al. Attitudinal barriers to participation in oncology clinical trials: Factor analysis and correlates of barriers. Eur J Cancer Care 2015;24:28-38. (3) Kaplan CP, Napoles AM, Dohan D et al. Clinical trial discussion, referral, and recruitment: Physician, patient, and system factors. Cancer Causes Control 2013;24:979-988. (4) Mills EJ, Seely D, Rachlis B et al. Barriers to participation in clinical trials of cancer: A meta-analysis and systematic review of patient-reported factors. Lancet Oncol 2006;7:141-148. (5) Seruga B, Sadikov A, Cazap EL et al. Barriers and challenges to global clinical cancer research. Oncologist 2014;19:61-67. (6) Hastings CE, Fisher CA, McCabe MA et al. Clinical research nursing: A critical resource in the national research enterprise. Nurs Outlook 2012;60:149-156. (7) Lepers S, Ottevaere A, Oyen C et al. The challenge of molecular testing for clinical trials in advanced non-small cell lung cancer patients: analysis of a prospective database. J.Thorac.Oncol. 2015; 10 Suppl: Mini Oral presentation WCLC 2015. (8) Adam V, Dooms C, Vansteenkiste J. Lung cancer at the intensive care unit: The era of targeted therapy. Lung Cancer 2015;E-pub May 18.
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P2.03 - Poster Session/ Treatment of Locoregional Disease – NSCLC (ID 213)
- Event: WCLC 2015
- Type: Poster
- Track: Treatment of Locoregional Disease – NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P2.03-023 - In-Field Nodal Relapse after Irradiation for Locally Advanced Non-Small-Cell Lung Cancer: Is There a Dose-Effect Relationship? (ID 3201)
09:30 - 09:30 | Author(s): C. Dooms
- Abstract
Background:
We investigated whether prescribed radiation dose is related to in-field nodal relapse. Since in-field nodal relapse is rare according to current literature, the influence of radiation dose on the incidence could be questioned.
Methods:
A retrospective analysis of prospective data was performed. Pathologic lymph nodes were registered based on RECIST 1.1 criteria. An in-field nodal relapse is defined as an increase of at least 20% of the short axis diameter and a minimum absolute increase of 2 mm, taking as reference the short axis diameter measured 3 months (+/-2 months) after radiation therapy. Three subgroups were defined based on EQD2,T (group A: EQD2,T < 50 Gy, group B: EQD2,T 50-55 Gy, group C: EQD2,T > 55 Gy). An actuarial Kaplan-Meier analysis was performed to evaluate the cumulative proportion of in-field nodal relapse per subgroup. A Cox proportional hazards regression analysis was performed to take initial nodal diameter into account.
Results:
A total of 75 patients were reviewed. Sixty-two patients (83%) had stadium IIIA/IIIB disease. Twelve patients (16%) had stadium IV NSCLC who were treated with a radical oligometastatic approach. One patient (1%) had stadium IIB disease. Sixteen patients (21%) were treated with radiotherapy alone (38% group A, 25% group B, 38% group C). Sequential chemoradiotherapy was given in 47 patients (63%) (32% group A, 45% group B and 23% group C). Twelve patients (16%) received concurrent chemoradiotherapy (33% group A, 66% group B). Group A consisted of 25 patients (median age: 65 years (range 45-88), median follow-up: 6 months (range 1-54)). Thirty-three patients were included in group B (median age: 59 years (range 45-80), median follow-up: 8 months (range 1-86)). Group C consisted of seventeen patients (median age: 67 years (range 54-83), median follow-up: 9 months (range 2-45)). In all three groups median number of follow-up CT scans is 2 (range of 1-11 for group A and C, range of 1-13 for group B). Any relapse occurred in fifty-eight patients (77,3%). Nineteen patients (33%) had a locoregional failure only. Twenty-two patients (38%) had distant failure only, either by progression of a known metastasis or occurrence of a new distant lesion. Seventeen patients (29%) had a locoregional and distant failure at once. A total of 142 lymph nodes were taken into account (55 (39%) in group A, 52 (37%) in group B and 35 (25%) in group C). The average baseline short axis diameter per group was 16,3 mm, 15,8 mm and 14,6 mm for group A, B and C respectively. An actuarial Kaplan-Meier analysis performed on all lymph nodes (n=142) showed no significant difference between subgroups (p=0,24). A Cox proportional hazards regression analysis didn’t show a significant effect of baseline nodal diameter on in-field nodal relapse (p=0,82).
Conclusion:
Prescribed radiation dose is not related to the occurrence of in-field nodal relapse. There was no relation between initial lymph node diameter and in-field nodal relapse.
