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R. Buettner
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ORAL 06 - Next Generation Sequencing and Testing Implications (ID 90)
- Event: WCLC 2015
- Type: Oral Session
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 2
- Moderators:G. De Lima Lopes, V. Miller
- Coordinates: 9/07/2015, 10:45 - 12:15, Mile High Ballroom 1a-1f
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ORAL06.01 - Genomic Characterization of Large-Cell Neuroendocrine Lung Tumors (ID 1667)
11:05 - 11:16 | Author(s): R. Buettner
- Abstract
Background:
Neuroendocrine lung tumours account for 25% of all lung cancer cases, and they range from low-aggressive pulmonary carcinoids (PCA) to highly malignant small-cell lung cancer (SCLC) and large-cell neuroendocrine lung carcinoma (LCNEC). The last two are strongly associated with heavy smoking and are typically detected at a clinically advanced stage, having a poor survival. Comprehensive genomic analyses in lung neuroendocrine tumours are difficult because of limited availability of tissue. While more effort has been done in the context of SCLC, the detailed molecular features of LCNEC remain largely unknown.
Methods:
We conducted 6.0 SNP array analyses of 60 LCNEC tumours, exome sequencing of 55 tumor-normal pairs, genome sequencing of 11 tumour-normal pairs, transcriptome sequencing of 69 tumours, and expression arrays on 60 tumors. Data analyses were performed using in house developed and published pipelines.
Results:
Analyses of chromosomal gene copy number revealed amplifications of MYCL1, FGFR1, MYC, IRS2 and TTF1. We also observed deletions of CDKN2A and PTPRD. TTF1 amplifications are characteristic of lung adenocarcinoma (AD); CDKN2A deletions are frequent alterations in both AD and squamous-cell lung carcinoma (SQ); FGFR1 amplifications are found in SQ and, less frequently, in SCLC; and MYCL1 and IRS2 amplifications are frequent events in SCLC. Similar to the copy number data, we found patterns of mutations characteristic of other lung cancer subtypes: TP53 was the most frequently mutated gene (75%) followed by RB1 (27%), and inactivation of both TP53 and RB1, which is the hallmark of SCLC, occurred in 20% of the cases. Mutations in STK11 and KEAP1-NFE2L2 (frequently seen in AD and SQ) were found in 23% and 22% of the specimens, respectively. Interestingly, mutations in RB1 and STK11/KEAP1 occurred in a mutually exclusive fashion (p-value=0.016). Despite the heterogeneity observed at the mutation level, analysis of the pattern of expression of LCNEC in comparison with the other lung cancer subtypes (AD, SQ, SCLC, and PCA) points to LCNEC as being an independent entity. An average mutation rate of 10.7 mutations per megabase was detected in LCNEC, which is in line with the rate observed in other lung tumours associated with smoking. We found that, similar to SCLC, the mutation signatures associated with APOBEC family of cytidine deaminases, smoking, and age (based on Alexandrov et al 2013) were the predominant ones in LCNEC. However, the contribution of the individual SCLC and LCNEC samples to these three signatures was quite different, and we are currently exploring it.
Conclusion:
Taking into account somatic copy number and mutation data, we distinguished two well-defined groups of LCNEC: an SCLC-like group, carrying alterations in MYCL1, ISR2, and in both RB1 and TP53; and a group resembling AD and SQ, with alterations in CDKN2A, TTF1, KEAP1-NFE2L2, and STK11. Although these results suggest that LCNEC might be a mix of different lung cancer subtypes, mutation clonality and expression analyses show that they are likely to be a separate entity, sharing molecular characteristics with the other lung cancer subtypes. Their heterogeneity suggests that LCNEC might represent an evolutionary trunk that can branch to SCLC or AD/SQ.
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ORAL06.07 - An Integrated Cost-Effectiveness and Outcome Analysis Based on Multiplex Lung Cancer Genotyping in the Network Genomic Medicine (ID 2800)
12:10 - 12:21 | Author(s): R. Buettner
- Abstract
Background:
The Network Genomic Medicine (NGM) Lung Cancer is an interdisciplinary and intersectoral network offering comprehensive and centralized next generation sequencing (NGS)-based multiplex genotyping for all inoperable lung cancer patients in Germany. In 2014 NGM and the AOK Rheinland/Hamburg, one of the largest German public health insurances, have successfully contracted and established the first "flat rate" cost reimbursement model for NGS-based comprehensive lung cancer genotyping in Europe. After a year the first joint health-economic evaluation of NGM patients was initiated.
Methods:
The AOK Rheinland/Hamburg cooperates with NGM within the integrated care contract (ICC) according to § 140 German Social Insurance Code. Besides the cost reimbursement model for the NGS-based diagnostics the ICC comprises optional second opinion consultation hours and a joint evaluation program. The NGS panel used for all patients currently consists of 14 genes and 102 amplicons to cover potentially targetable aberrations. Other German public and private health insurances are currently negotiating to join the ICC. In April 2015 we elaborated a model to analyze molecularly guided therapy cost and outcome of inoperable lung cancer patients integrating health insurance cost data (diagnostic, therapy and drug-related costs). This model includes NGS-based molecular diagnostic results, treatment strategies and cost-effectiveness. Additionally, time-points of molecular genotyping and their influence on patient-related outcome and quality of life will be examined.
Results:
In 2014 about 4500 lung cancer NGM patients were centrally genotyped on the central NGS platform in Cologne. Since April 2014 167 patients, insured by the AOK Rheinland/Hamburg, consented for ICC. 149 patients received NGS-based molecular diagnostic of their tumors. 18 samples were not suitable for testing. ICC patients were stratified according to their molecular diagnostic results and molecular guided therapy options (targeted drugs including off-label use, participating in clinical trials or standard chemotherapy). Clinical outcome data were collected within NGM (by over 200 clinical partners) and reimbursement data are provided by the AOK Rheinland/Hamburg. This model will be extended to all NGM patients independent of their insurance status. Final cost-effectiveness and outcome data will be presented.
Conclusion:
NGM stands for the implementation of personalized cancer therapy into clinical routine in Germany. Now we systematically evaluate NGS-based molecular results, clinical outcome and cost-effectiveness data besides of clinical trials. First-time in Europe data evaluation is provided in a close cooperation between health care providers and health insurance companies and even matching the patient’s data. Furthermore, in 2015 a joint database (NGM Cancer Information System) for retrospective evaluation of personalized cancer treatment in Germany will be launched. Our model of implementing personalized cancer care in broad clinical routine is currently transferred to other tumor entities.
