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X. Lu
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MINI 13 - Genetic Alterations and Testing (ID 120)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:Y. Koh, R.K. Thomas
- Coordinates: 9/08/2015, 10:45 - 12:15, 205+207
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MINI13.03 - Characterization of MET Gene and MET Protein Expression in Lung Cancer (ID 2155)
10:55 - 11:00 | Author(s): X. Lu
- Abstract
- Presentation
Background:
Activation of the MET signaling pathway can propel the growth of cancer cells in non-small cell lung cancer (NSCLC). Increased MET gene by amplification and/or polysomy can cause MET protein overexpression; less common causes include mutations, translocations, and alternative RNA splicing. Clinical trials using MET as a biomarker for selection of lung cancer patients who might most benefit from targeted therapy have experienced variable outcomes. We aimed to characterize the relationship between MET protein overexpression and MET amplification or mean copy number alterations in patients with NSCLC.
Methods:
The Lung Cancer Mutation Consortium (LCMC) is performing an ongoing study of biomarkers with patients with NSCLC from 16 cancer center sites across the United States. For this analysis, 403 cases had complete data for MET protein expression by immunohistochemistry (IHC, monoclonal antibody SP44, Ventana) and MET gene amplification by fluorescence in-situ hybridization (FISH, MET/CEP7 ratio). Pathologists evaluated MET expression using the H-score, a semi-quantitative assessment of the percentage of tumor cells with no, faint, moderate, and/or strong staining, ranging from 0-300. Spearman's correlation was used to analyze the correlation between MET protein expression (H-scores) and FISH results (MET/CEP7 ratio (N=403) and MET copy number (N=341). Protein overexpression using 5 different cut-offs was compared with amplification defined as MET/CEP7 ≥ 2.2 and high mean copy number defined as ≥ 5 MET gene copies per cell using the Fisher’s exact test. Cox Proportional Hazards models were built to examine the associations of these different definitions of positivity with prognosis, adjusting for stage of disease.
Results:
MET protein expression was significantly correlated with MET copy numbers (r=0.17, p=0.0025), but not MET/CEP7 ratio (r=-0.013, p=0.80). No significant association was observed between protein overexpression using a commonly used definition for MET positivity (“at least moderate staining in ≥ 50% tumor cells”) and MET amplification (p=0.47) or high mean copy number (p=0.09). A definition for MET protein overexpression as “≥ 30% tumor cells with strong staining” was significantly associated with both MET amplification (p=0.03) and high mean copy number (p=0.007), but a definition of “≥ 10% tumor cells with strong staining” was not significantly associated with either. Definitions of protein overexpression based on high H-scores (≥200 or ≥250) were associated with high MET mean copy numbers (p=0.03 and 0.0008, respectively), but not amplification (p=0.46 and 0.12, respectively). All 5 definitions of MET protein overexpression demonstrated a significant association with worse prognosis by survival analyses (p-values ranged from 0.001 to 0.03). High MET copy number (p=0.045) was associated with worse prognosis, but MET amplification was not (p=0.07).
Conclusion:
Evaluation of NSCLC specimens from LCMC sites confirms that MET protein expression is correlated with high MET copy number and protein overexpression is associated with worse prognosis. Definitions of MET protein overexpression as “an H-score ≥250” and “≥30% tumor cells with strong staining” were significantly associated with high mean MET copy number. It may be worth reevaluating the performance of MET as a biomarker by different definitions of positivity to predict response to MET-targeted therapies.
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MINI 29 - Meta Analyses and Trial Conduct (ID 156)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Treatment of Advanced Diseases - NSCLC
- Presentations: 1
- Moderators:D. Morgensztern, M. Redman
- Coordinates: 9/09/2015, 18:30 - 20:00, Mile High Ballroom 2a-3b
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MINI29.07 - CNS Disease Enrollment Criteria for NSCLC Drug Trials (ID 908)
19:05 - 19:10 | Author(s): X. Lu
- Abstract
- Presentation
Background:
CNS metastases are common in NSCLC, yet clinical trials of new drugs in NSCLC have widely varying inclusion and exclusion criteria in relation to CNS disease. CNS disease that has received local therapy may be dormant, confounding any subsequent drug benefit, whereas untreated CNS disease may reduce PFS if CNS and systemic drug exposure differs. Recently, RANO guidelines propose explicitly explored activity in CNS disease within solid tumor drug trials. The true extent of variation in CNS related enrollment criteria in NSCLC clinical trials has not been documented before.
Methods:
ClinicalTrials.gov was interrogated on September 11, 2014 looking for interventional drug trials including advanced NSCLC. The following characteristics were extracted: 1) trial phase; 2) experimental arm therapy (chemotherapy, targeted therapy, immunotherapy, anti-angiogenic); 3) location (US, International only, US + International); 4) sponsor (Industry, University/IIT, Cooperative Group, NCI); 5) CNS disease allowance (strict exclusion, allowed after local treatment (surgery/radiation), unrestricted/untreated disease allowed). Industry sponsorship was divided into ‘large pharmaceutical’, (top decile by number of sponsored trials) and ‘small pharmaceutical’ (lower 9 deciles). Exclusion of CNS metastasis was treated as a binary variable and grouped as ‘strict exclusion’ vs. ‘allowed CNS metastasis’ (‘allowed with treatment’ and ‘allowed untreated’). Univariable and multivariable logistic regression models were fit to test the association between exclusion of CNS metastasis and trial characteristics. Statistical significance was set at 0.05 with no adjustment for multiple testing.
Results:
Of 735 trials involving NSCLC, 325 (44%) were excluded from analysis mostly because of allowance of early stage NSCLC (50%, n=164), or no active therapy inclusion (45%, n=146). In the remaining 406 trials, patients with CNS metastases were excluded in 58 (14%), allowed after local treatment in 165 (41%), and allowed with no prior treatment in 104 (26%). CNS criteria were not referenced in the available information in 79 (19%) trials which were excluded from further analysis. On univariable analysis, the odds of CNS metastasis exclusion on trial were significantly lower in trials with vs. without targeted therapy (OR 0.44, 95% CI: 0.25-0.78, p=0.005) and significantly higher in trials with vs. without immunotherapy (OR 2.13, 95% CI: 1.06-4.28, p=0.04). No other univariable associations were significant. In multivariable analysis, after adjustment for all other factors, only trials located at international only vs. US only sites had greater odds of exclusion of CNS metastasis (OR 1.64, 95% CI 0.84-3.22; p=0.03).
Conclusion:
Although univariable analysis suggests class of agent may influence trial design, in multivariable analysis trial location was the only variable associated with strict exclusion of CNS metastases. This raises the possibility of exclusion based on historical/cultural rather than scientific factors. With 18% of trials (58/327) excluding all CNS disease and 50% (165/327) only allowing CNS disease if previously treated, less than a third of NSCLC trials permit unequivocal assessment of CNS activity (104/327). Given the high frequency of CNS disease in NSCLC, sponsors should consider consciously tailoring trial designs to more explicitly explore efficacy in this patient population.
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ORAL 25 - Biology and Other Issues in SCLC (ID 125)
- Event: WCLC 2015
- Type: Oral Session
- Track: Small Cell Lung Cancer
- Presentations: 1
- Moderators:J. Sage, L. Montuenga
- Coordinates: 9/08/2015, 10:45 - 12:15, 605+607
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ORAL25.06 - Association of Expression of PD-L1 with the Tumor Immune Microenvironment in Small Cell Lung Cancer (ID 859)
11:39 - 11:50 | Author(s): X. Lu
- Abstract
- Presentation
Background:
Small cell lung cancer (SCLC) accounts for 15% of all lung cancers and has been under-studied relative to novel therapies. Therapeutic antibodies to immune checkpoints are showing promising clinical results. Programmed death-ligand 1 (PD-L1), which can be expressed on many cancer and immune cells, plays an important role in blocking the cancer immunity cycle by binding programmed death-ligand 1 receptor (PD-1), which is a negative regulator of T-lymphocyte activation. Since knowledge about PD-L1 expression in SCLC is limited, we aimed to characterize PD-L1 expression in a cohort of 98 SCLC patients.
Methods:
PD-L1 protein expression and mRNA levels were determined by immunohistochemistry (IHC, SP142, Spring Bioscience) and mRNA in situ hybridization (ISH) in primary tumor tissue microarrays obtained from 98 SCLC patients. Membranous staining of PD-L1 protein and mRNA expression on tumor cells and protein expression on tumor-infiltrating immune cells (TIICs) were scored separately using semi-quantitative scores (H-score 0-300 and RNA score 0-4). An H-score ≥ 5 and an RNA score > 2 were defined as the cutoffs for PD-L1 protein and RNA expression positivity. The degree of TIICs was semi-quantitatively scored on hematoxylin and eosin-stained TMA slides as having “0” (no), “1” (mild), “2” (moderate), or “3” (marked) infiltration. The data was analyzed using the Fisher’s exact test, Spearman correlation, two-sample t-test, log-rank test and Kaplan- Meier survival analysis with significance level assumed to be 0.05.
Results:
3.16% of cases (3/95) were positive for PD-L1 protein expression in tumor cells, and 30.21% were positive for PD-L1 in TIICs (29/96, p<0.0001). PD-L1 mRNA expression was positive in 15.46% of the tumor cells (15/97). PD-L1 protein and mRNA expression on tumor cells demonstrated a positive correlation (p<0.0001, r=0.431). PD-L1 mRNA expression on tumor cells positively correlated with PD-L1 protein expression on TIICs (p<0.0001, r=0.354). The degree of TIICs positively correlated with both PD-L1 protein expression in tumor cells (p=0.011, r=0.264) and PD-L1 mRNA expression in tumor cells (p<0.0001, r=0.405). The degree of TIICs positively correlated with PD-L1 protein expression in TIICs (p<0.0001, r=0.625). The only significant association observed between PD-L1 expression with clinical characteristics or prognosis of the 78 SCLC patients with clinical data, was between age of patients and PD-L1 protein (p<0.0001) and mRNA expression (p=0.0006) on tumor cells.
Conclusion:
A subset of SCLCs is characterized by positive PD-L1 protein and/or mRNA expression in tumor cells and TIICs. PD-L1 mRNA expression was more frequently positive than PD-L1 protein expression in the tumor cells. PD-L1 protein expression was expressed more in TIICs than tumor cells. Higher PD-L1 protein and mRNA expression correlated with more infiltration of TIICs. PD-L1 expression represents the immune response in SCLC. The microenvironment may play a major role on the PD-1/PD-L1 pathway of SCLC. SCLC Patients with PD-L1 expression may respond to anti-PD-L1 treatment.
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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): X. Lu
- 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): X. Lu
- 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.
