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D. Gao
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ORAL 37 - Novel Targets (ID 146)
- Event: WCLC 2015
- Type: Oral Session
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:S.S. Ramalingam, E. Thunnissen
- Coordinates: 9/09/2015, 16:45 - 18:15, Mile High Ballroom 4a-4f
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ORAL37.06 - Defining MET Copy Number Driven Lung Adenocarcinoma Molecularly and Clinically (ID 2379)
17:39 - 17:50 | Author(s): D. Gao
- Abstract
- Presentation
Background:
Increases in MET copy number define an oncogenic driver state sensitive to MET inhibition (Camidge et al, ASCO 2014). However, the level at which the genomic gain is relevant remains uncertain. When testing is performed by fluorescence in situ hybridization (FISH), variable cut-points in both mean MET/cell and MET/CEP7 ratio have been used. Partially overlapping datasets from the Lung Cancer Mutation Consortium (LCMC1) and Colorado Molecular Correlates (CMOCO) Laboratory were explored for a distinct MET-copy number driven lung adenocarcinoma subtype.
Methods:
MET was assessed by FISH. Data from non-adenocarcinomas and EGFR mutant patients with acquired resistance to an EGFR inhibitor were excluded. Positivity criteria were mean MET/cell ≥5 (low ≥5-<6, intermediate ≥6-<7, high ≥7) or MET/CEP7 ≥1.8 (low ≥1.8-≤2.2, intermediate >2.2-< 5, high ≥5). MET metrics were compared by race, sex, smoking status, stage at diagnosis, number of metastatic disease sites, site of metastases, presence of other known drivers (EGFR, KRAS, ALK, ERBB2, BRAF, NRAS, ROS1 and RET), response to first line chemotherapy and overall survival using Fisher’s exact tests, chi-square tests, Spearman correlations and log-rank tests, as appropriate. Statistical significance was set at the 0.05 level without adjustment for multiple comparisons.
Results:
1164 unique adenocarcinomas were identified (60% female, 85% Caucasian, 66% ex/current smokers). MET/CEP 7 data was available on 1164 and mean MET/cell on 700. 52/1164 (4.5%) had MET/CEP7 ≥1.8 (48% female, 83% Caucasian, 69% smokers). 50/52 (98%) had ≥1 other oncogenic driver tested (25/50 (50%) positive). 113/700 (16%) had mean MET/cell ≥ 5 (57% female, 82% Caucasian, 58% smokers). 109/113 (96%) had ≥ 1 other oncogenic driver tested (73/109 (67%) positive). Among patients with ≥1 additional driver oncogene tested, alternate drivers in low, indeterminate and high categories of mean MET/cell were 44/60 (67%), 17/24 (70%) and 12/28 (43%) respectively and for MET/CEP7: 16/29 (55%), 9/18 (50%) and 0/4 (0%) respectively. MET positive with additional drivers were excluded from further analyses. Men exceeded women in MET/CEP7 (men 4% vs women 1.6%, p = 0.019) and mean MET/cell positive cases (men 9.6% vs women 5.4%, p = 0.058). 6.4% of adrenal metastasis cases were MET/CEP7 positive vs 2% all other sites, p=0.031. Mean MET/cell: 12% adrenal vs 5% other sites, p=0.082. MET/CEP7 or mean MET/cell positive and negative groups did not differ by other variables (p > 0.05).
Conclusion:
The proportion of ‘MET positive’ adenocarcinomas varies by definition and positivity cut-point. Mean MET/cell ≥5 defines nearly 4x more positives than MET/CEP7 ≥1.8 and no mean MET/cell positive category was free from overlap with other drivers. As only high MET/CEP7 had no overlap with other drivers, MET/CEP7 ≥ 5 is the clearest candidate for a pure MET-copy number driven state, however cases free from other drivers do exist at lower MET positivity levels. MET/CEP7 positive cases free from other known drivers are more likely to be male, but unlike other known oncogenic states, race and smoking status are not significant in determining positivity. MET positivity may have a specific biological phenotype, being more likely to present with adrenal metastases.
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P2.04 - Poster Session/ Biology, Pathology, and Molecular Testing (ID 234)
- Event: WCLC 2015
- Type: Poster
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P2.04-006 - MiRNA Signature to Assess Sensitivity to FGFR Tyrosine Kinase Inhibitors (ID 1717)
09:30 - 09:30 | Author(s): D. Gao
- Abstract
Background:
Increased signaling through the FGF/FGFR signaling pathway has been implicated as a driver in a number of different malignancies including lymphomas, prostate cancer, breast cancer, and lung cancer. This pathway also appears to play a role in conferring de novo and acquired resistance to cancers driven by EGFR mutations. Consequently, drugs that inhibit FGFRs are being investigated as potential therapeutics for cancer. Here we screened a large panel of miRNAs as potential predictors of sensitivity to FGFR tyrosine kinase inhibitors (TKIs).
Methods:
A panel of 377 miRNAs (Megaplex Card A, Life Technologies) was screened for expression level differences between four lung cancer cell lines that are sensitive (IC~50~< 50 nM) and four lines that are resistant (IC~50~ > 100 nM) to ponatinib (non-specific FGFR TKI) and AZD4547 (FGFR-specific TKI). Expression levels were assayed by RT-qPCR and analyzed using the Statistical Analysis of Microarrays (SAM) method. Thirty-nine miRNAs having an estimated false discover rate (FDR) of zero and large median fold differences (> 8) between the sensitive and resistant lines were selected for signature development. RT-qPCR assays were incorporated into a custom microfluidics card (Life Technologies), which was used to profile the original 8 cell lines and 10 additional sensitive lines and 16 additional resistant lines (34 lines total). Logistic regression was then used to identify the best signature panel for distinguishing sensitive cell lines from resistant.
Results:
Univariate analysis indicated three miRNAs (let-7c, miR-338, and miR-218) that differed between the sensitive and resistant lines at p < .05. The best signature panel consisted of let-7c, miR-200a and miR-200b, which gave an area under the receiver operator characteristic (AUROC) curve of 0.90 (95% CI = 0.8 to 1). This performance was nearly as good as using FGFR1 mRNA alone (AUROC = 0.94). The predominant miRNA in our 3-miRNA signature was let-7c, which also exhibited a suggestive additive effect to using FGFR1 as a biomarker (p = 0.09). We also tested whether cell lines with high sensitivity to ponatinib can be made resistant by reducing the high level of let-7c in these lines. We have found that transient transfection of let-7c silencing RNA (Life Technologies) produces a decrease in FGFR1 mRNA levels for some cell lines but not others.
Conclusion:
It appears possible to predict sensitivity to an FGFR1 inhibitor using miRNA expression signatures. More studies, however, are needed to confirm the 3-marker signature developed in this study. Modulating let-7c, the predominant predictor within the signature, appears to modulate FGFR1 levels in a manner consistent with altering ponatinib sensitivity. This effect is most likely indirect as the mRNA of FGFR1 does not contain predicted binding sites for let-7c.
