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Rolf A Stahel
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MA 06 - Lung Cancer Biology I (ID 660)
- Event: WCLC 2017
- Type: Mini Oral
- Track: Biology/Pathology
- Presentations: 1
- Moderators:N. Motoi, Keith M Kerr
- Coordinates: 10/16/2017, 15:45 - 17:30, Room 501
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MA 06.06 - Assessment of RANK Prevalence and Clinical Significance in the NSCLC European Thoracic Oncology Platform Lungscape Cohort (ID 10006)
15:45 - 17:30 | Author(s): Rolf A Stahel
- Abstract
- Presentation
Background:
Receptor Activator of Nuclear Factor κappa-B (RANK) is a pathway involved in bone homeostasis. Recent evidence suggests that RANK signalling may also play a role in bone metastasis, and primary breast and lung cancers. The European Thoracic Oncology Platform (ETOP) Lungscape project allows evaluation of the prevalence of RANK expression and its clinical significance in a cohort of surgically-resected NSCLCs.
Method:
RANK expression was assessed on tissue microarrays (TMAs) using immunohistochemistry. Up to 4 cores per patient were analysed based on sample acceptance criteria. An H-Score (staining intensity + % cells stained) was used to assess RANK expression (positivity), as defined by at least 1 core with any degree of positive staining. Prevalence of RANK positivity and its association with clinicopathological characteristics, other cancer-related biomarkers (IHC ALK/MET/PTEN/PD-L1 expression and EGFR/KRAS/PIK3CA mutations) and patient outcome [Relapse-free Survival (RFS), Time-to-Relapse (TTR), Overall Survival (OS)] was explored in a subset of the ETOP Lungscape cohort. The prevalence of RANK overexpression (proportion of positive cancer cells ≥50%) was also investigated.
Result:
RANK expression was assessed in patients from 3 centers, a total of 402 from the 2709 patients of the Lungscape cohort, with median follow-up 44 months; 32.6% female, 40.8/54.2/5.0% adenocarcinomas (AC)/squamous cell carcinomas (SCC)/other, 44.8/28.4/26.9% with stage I/II/III, 20.6/57.7/18.9% current/former/never smokers (and 2.7% with unknown smoking status). Median was 74 months for both RFS and OS, while median TTR was not reached. Prevalence of RANK positivity was 26.6% (107 of the 402 cases), with 95% confidence interval (95%CI):22.4%-31.2%; significantly higher in AC: 48.2% (79 of 164 cases), 95%CI:40.3%-56.1%; vs SCC: 9.2% (20 of 218 cases), 95%CI:5.7%-13.8%; (p<0.001). RANK positivity was more frequent in females (38.9% vs 20.7% in males, p<0.001) and tumors≤4cm (30.7% vs 21.1% in tumors>4cm, p=0.031). Significant associations were also detected between RANK and PTEN expression in AC (RANK positivity 57.4% in PTEN expression vs 30.5% in PTEN loss; p=0.0011) and with MET status in SCC (RANK positivity 27.8% in MET+ vs 7.6% in MET-; p=0.016). No association with outcome was found. RANK overexpression was identified in 43 (10.7%; 95%CI: 7.9%-14.1%) cases.
Conclusion:
In this early-stage NSCLC cohort, RANK positivity (26.6% overall) is found to be significantly more common in adenocarcinomas (48.2%), females, patients with tumors of smaller size, with PTEN expression (in SCC) and MET positivity (in AC). No prognostic significance of RANK expression was found. Analysis of additional cases is ongoing and results will be presented.
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MA 15 - Lung Cancer Biology II (ID 670)
- Event: WCLC 2017
- Type: Mini Oral
- Track: Biology/Pathology
- Presentations: 1
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MA 15.11 - CCNE1, PTGS2, TGFA and WISP2 Predict Benefit from Bevacizumab and Chemotherapy in Patients with Advanced Non-Small Cell Lung Cancer (SAKK19/09) (ID 9592)
15:45 - 17:30 | Author(s): Rolf A Stahel
- Abstract
- Presentation
Background:
Bevacizumab (Bev; Avastin[®]) is a monoclonal antibody against the vascular endothelial growth factor. No predictive biomarkers for the use of Bev have been established so far. We aimed identifying genes predictive for progression-free survival (PFS) and overall survival (OS) of patients treated in the trial SAKK19/09 (NCT01116219).
Method:
SAKK19/09 was a non-randomized phase II trial with two sequential cohorts including patients with non-squamous NSCLC and EGFR wild-type. In Cohort 1, 77 patients were treated with cisplatin (C) 75mg/m[2], pemetrexed (Pem) 500mg/m[2] and Bev 7.5mg/kg, followed by Bev+Pem maintenance. Cohort 2 included 52 patients treated with C+Pem followed by Pem maintenance. RNA was isolated from baseline tumor tissue sections and processed for gene expression analysis by Nanostring. Using the Nanostring nCounter® System (Nanostring Technologies) gene expression of 201 genes, including 6 housekeeping genes was measured using a custom-designed codeset. For each gene, a Cox regression was performed with normalized gene expressions, treatment and the interaction for PFS and OS. No adjustment for multiple testing was done.
Result:
We analyzed 99 patient samples (61 in Cohort 1; 38 in Cohort 2) with 201 genes at baseline. We found 7 genes potentially predictive for PFS (AURKB, CCNE1, CDKN2B, MMP2, PTGS2, TGFA, WISP2), 4 of which were also potentially predictive for OS (CCNE1, PTGS2, TGFA and WISP2) (Table 1).Gene Accession HR (95% confidence interval) p-value of interaction Cohort 1 Cohort 2 Potential predictive markers for PFS AURKB NM_004217 1.09 (0.84-1.42) 0.78 (0.61-0.99) 0.0481 CCNE1 NM_001238 1.09 (0.87-1.36) 0.73 (0.53-1.02) 0.0312 CDKN2B NM_004936.3 0.80 (0.67-0.95) 1.10 (0.85-1.43) 0.0375 MMP2 NM_004530.2 0.81 (0.67-0.97) 1.10 (0.91-1.34) 0.0258 PTGS2 (COX-2) NM_000963.1 1.29 (1.06-1.58) 0.90 (0.78-1.04) 0.00352 TGFA NM_003236.2 1.13 (0.94-1.37) 0.74 (0.53-1.03) 0.0452 WISP2 NM_003881.2 0.82 (0.69-0.98) 1.24 (1.02-1.51) 0.0015 Potential predictive markers for OS CCNE1 NM_001238 1.08 (0.86-1.36) 0.71 (0.49-1.02) 0.0324 PTGS2 (COX-2) NM_000963.1 1.35 (1.10-1.65) 0.81 (0.69-0.95) <0.0001 TGFA NM_003236.2 1.17 (0.96-1.43) 0.55 (0.33-0.91) 0.00352 WISP2 NM_003881.2 0.87 (0.73-1.03) 1.14 (0.92-1.42) 0.0314
Conclusion:
We identified several potentially predictive genes for Bev activity in combination with chemotherapy. Several of these (AURKB, CCNE1, CDKN2B, TGFA) have previously been shown to play an important role in cell cycle regulation and cell proliferation supporting the hypothesis that Bev supports chemotherapy activity. Notably, also a gene involved in inflammation (PTGS2) was significantly predictive for outcome. Further work is ongoing to explore changes in gene expression using tumor rebiopsies at progression.
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MS 18 - Biomarker for Anti-PD-L1 Therapy (ID 540)
- Event: WCLC 2017
- Type: Mini Symposium
- Track: Immunology and Immunotherapy
- Presentations: 1
- Moderators:Yuichi Ishikawa, Sanja Dacic
- Coordinates: 10/17/2017, 15:45 - 17:30, Main Hall
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MS 18.03 - Potential Application of Molecular Genomic for Immunotherapy (ID 7645)
15:45 - 17:30 | Presenting Author(s): Rolf A Stahel
- Abstract
- Presentation
Abstract not provided
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P1.09 - Mesothelioma (ID 695)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Mesothelioma
- Presentations: 1
- Moderators:
- Coordinates: 10/16/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P1.09-001 - Multiplexed Biomarker Strategies Based on Targeted Proteomics for Detection of Malignant Pleural Mesothelioma in Blood (ID 8811)
09:30 - 16:00 | Author(s): Rolf A Stahel
- Abstract
Background:
Blood biomarkers are only infrequently used for the diagnosis of malignant pleural mesothelioma. Most of these biomarkers are single marker proteins relying on antibody assays and with limited accuracy for mesothelioma detection in the blood. In our study, we apply targeted proteomics technologies to investigate novel diagnostic strategies based on multiplexed protein biomarkers for mesothelioma detection in serum.
Method:
We studied more than 400 serum samples of early (I/II) and late stage (III/IV) mesothelioma and asbestos exposed donors collected in USA, Australia and Europe. For quantitative proteomics, 50 µl of serum were processed on 96-well plates over different days to enrich for N-linked glycoproteins based on hydrazide chemistry. After tryptic digestion, serum peptides were analyzed in replicates, separated by ultra-performance liquid chromatography followed by selected reaction monitoring on a triple quadrupole mass spectrometer (LC-SRM). Isotopically labeled peptides were spiked in each sample for quantification and to assess the performance of the LC-SRM platform. Two non-human N-linked glycoproteins were spiked in each serum sample before processing to monitor the performance of the targeted proteomics workflow across samples and plates. The software package MSstats was used for large scale quantitative data analysis.
Result:
We processed and quantified over 400 serum samples analyzed in LC-SRM replicates. We assessed the performance of the targeted proteomics platform for large scale quantification of a multiplexed six peptide signature (including peptides from the established mesothelin biomarker). The coefficient of variation (CV) for parallel peptide quantification on LC-SRM ranged from 2% to 11.4% with CVs below 8% for all peptides but for one. Based on quantification of the two non-human spiked-in glycoproteins, average standard deviation of the targeted proteomics workflow was 0.42 over all samples. We investigated the performance of the multiplexed six peptide signature in discriminating mesothelioma from asbestos exposed donors. For the signature we fit a multiple logistic regression model on a training set of 212 patients and a validation set of 193 mesothelioma and asbestos exposed donors. The multiplexed biomarker signature discriminated mesothelioma from asbestos exposed with AUC of 0.72 in the validation set. Here, compared with performance of the single marker mesothelin (assessed by LC-SRM), the multiplexed biomarker signature separated early stage mesothelioma from asbestos exposed with AUC of 0.74, with sensitivity of 37.8% at 90% specificity, whereas the single mesothelin peptide had AUC of 0.66 and sensitivity of 22.2%.
Conclusion:
Multiplexed biomarker strategies based on targeted proteomics technologies can improve mesothelioma diagnosis in blood samples.
