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A.E. Barón



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    MINI 12 - Biomarkers and Lung Nodule Management (ID 109)

    • Event: WCLC 2015
    • Type: Mini Oral
    • Track: Screening and Early Detection
    • Presentations: 1
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      MINI12.02 - Clinical Utility of Chromosomal Aneusomy in High Risk Individuals (ID 1299)

      16:45 - 18:15  |  Author(s): A.E. Barón

      • Abstract
      • Presentation
      • Slides

      Background:
      In the context of CT screening in current and former smokers at high risk for lung cancer, the false positive rate is high (26% at first NLST screening; 13% with Lung-RADS criteria applied to NLST) and indeterminate nodules are frequently discovered. Noninvasive biomarkers are urgently needed to reduce false positives with screening CT and to improve risk stratification in those with indeterminate nodules. The Colorado (CO) Lung SPORE program performed a retrospective longitudinal evaluation (Pepe Phase 3 validation) to assess the potential of chromosomal aneusomy detected in sputum via fluorescence in situ hybridization (CA-FISH) as a biomarker for early detection in four nested case-control studies. Two of the cohorts (ACRIN/NLST and PLuSS) enrolled current and former smokers to investigate use of low dose CT to diagnose lung cancer. The other two were Colorado cohorts in which pulmonary clinic patients (mostly current and former smokers) were enrolled to investigate biomarkers to predict lung cancer. One of these cohorts (CO High Risk) was a COPD population and the other, still in the accrual phase, comprises patients referred for care of indeterminate lung nodules (CO Nodule).

      Methods:
      The cohorts were grouped into a Screening cohort (ACRIN/NLST (49 cases, 96 controls) and PLuSS (48 cases, 89 controls)) and a High Risk cohort (CO High Risk (55 cases, 59 controls) and CO Nodule (13 cases, 10 controls)). The CA-FISH assay was a 4-target panel including genomic sequences encompassing the EGFR and MYC genes, and the 5p15 and centromere 6 regions or the FGFR1 and PIK3CA genes. At the subject level, the assay was scored on a 4-category scale representing normal, probably normal, probably abnormal and abnormal. Operating characteristics (with 95% CI) of the assay were estimated for each group of cohorts overall and separately for COPD patients: sensitivity, specificity, likelihood ratio+ (LR+) and likelihood ratio- (LR-).

      Results:
      Using the cutoff of abnormal vs. not abnormal for CA-FISH, sensitivity and specificity for Screening subjects are 0.20 (0.13, 0.30) and 0.84 (0.78, 0.89), respectively; and for High Risk subjects are 0.67 (0.55, 0.78) and 0.94 (0.85, 0.98), respectively. Likelihood ratios for Screening subjects are LR+: 1.36 (0.81, 2.28) and LR-: 0.93 (0.83, 1.05), and for High Risk subjects are LR+: 11.66 (4.44, 30.63), and LR-: 0.34 (0.24, 0.48). Similar results were observed when only COPD subjects were analyzed.

      Conclusion:
      The high LR+ of sputum CA-FISH indicates that this noninvasive biomarker could be a clinically useful adjunct to CT among patients in high risk settings. Whether this same high level of LR+ will be reproducible in patients at high risk because of their indeterminate nodules remains to be seen. If so, a hypothetical patient with indeterminate nodules and a pre-test (CA-FISH) lung cancer risk of 20% would have a post-test probability of lung cancer of 78% if the CA-FISH test were positive. In the screening setting, however, the low LR+ of CA-FISH limits its clinical utility. Prospective assessment of sputum CA-FISH is ongoing in the Nodule Cohort of the CO Lung SPORE.

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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
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      MINI29.07 - CNS Disease Enrollment Criteria for NSCLC Drug Trials (ID 908)

      18:30 - 20:00  |  Author(s): A.E. Barón

      • Abstract
      • Presentation
      • Slides

      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 23 - Prevention and Cancer Risk (ID 121)

    • Event: WCLC 2015
    • Type: Oral Session
    • Track: Prevention and Tobacco Control
    • Presentations: 1
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      ORAL23.03 - Role of Inflammatory Infiltrates in Promoting Persistence or Regression of Bronchial Dysplasia (ID 3026)

      10:45 - 12:15  |  Author(s): A.E. Barón

      • Abstract
      • Presentation
      • Slides

      Background:
      Inflammatory infiltrates show differing capacities to eliminate malignant cells. This capacity is related to the polarization of key inflammatory cells in tumor infiltrates. A pathway analysis of genes that are differentially expressed between persistent and regressive bronchial dysplasia (BD) identified 13 pathways associated with persistence of which 8 were related to inflammation. We have hypothesized that differences in inflammatory infiltrate polarization may contribute to lung carcinogenesis and have employed gene expression and in situ analyses to characterize differences in inflammatory infiltrates related to persistence and regression of pre-malignant BD.

      Methods:
      Normalized gene expression levels (Affymetrix Hu 1.0) of selected genes related to inflammatory cell polarization features were analyzed to find differences associated with follow-up histology for BD. Validational analyses of these relationships were undertaken in studies of baseline biopsies selected to represent persistent (n=43) and regressive BD (n=39). These biopsies were analyzed by quantitative immunohistochemistry and dual immunofluorescence studies to characterize the overall proportion of subsets of T-lymphocytes and macrophages in each of the groups. Image analysis tools (Aperio) were used to characterize the density of inflammatory cell subsets in the stromal and epithelial compartments of biopsy tissue within defined areas.

      Results:
      Analysis of expression levels for a subset of inflammatory cell related genes assessed in a global gene expression analysis indicated significantly higher levels of expression of macrophage M1 markers HLA-DRA (p=0.01) and inducible nitric oxide synthetase (iNOS; p=0.02) and T-helper lymphocyte marker CD4 (p=0.04) in regressive BD compared to persistent BD. There was also a trend toward higher expression of cytotoxic T-lymphocyte marker CD8 in regressive BD (p=0.25). Expression of B-lymphocyte and neutrophil markers were not different between regressive and persistent BD. CD68 immunohistochemical stains (IHC) demonstrated a trend toward an increase in macrophages per area of combined dysplastic epithelium and underlying stroma with a mean increase in IHC positivity of 1.75-fold in regressive versus persistent BD (p=0.08). CD4 and CD8 IHC showed 1.36- and 1.19-fold increases, respectively, in regressive BD but these changes were not statistically significant (p=0.36 and p=0.43 respectively). Dual immunofluorescence was undertaken to determine if polarization specific subsets of macrophages correlated with regression or persistence of BD. Analysis of a preliminary subset of regressive (n=3) and persistent (n=3) BD demonstrates a wide range of M1 to M2 ratios (range = 0.84 – 4.82 for ratio of HLA-DRA-CD68 dual positive M1 to CD206-CD68 dual positive M2 macrophages per high power field, 400X). Additional analyses of macrophages are ongoing to determine if the polarization status is related to regression or persistence of BD, and analysis of markers of T-helper lymphocyte subsets are planned.

      Conclusion:
      Gene expression analyses indicate that increased expression of markers of M1 macrophages and T-helper lymphocytes are associated with regression, and in situ analyses suggest that differences in the amount of inflammatory cell subsets may be related to outcome in BD. These studies could have implications for predicting the behavior of premalignant disease and manipulating inflammatory activity in preventing progression of BD to invasive lung cancer.

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    ORAL 37 - Novel Targets (ID 146)

    • Event: WCLC 2015
    • Type: Oral Session
    • Track: Biology, Pathology, and Molecular Testing
    • Presentations: 1
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      ORAL37.06 - Defining MET Copy Number Driven Lung Adenocarcinoma Molecularly and Clinically (ID 2379)

      16:45 - 18:15  |  Author(s): A.E. Barón

      • Abstract
      • Presentation
      • Slides

      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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    P2.06 - Poster Session/ Screening and Early Detection (ID 219)

    • Event: WCLC 2015
    • Type: Poster
    • Track: Screening and Early Detection
    • Presentations: 1
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      P2.06-007 - A miRNA Signature Derived From Independently Replicated Biomarkers of Non-Small Cell Lung Cancer (ID 1728)

      09:30 - 17:00  |  Author(s): A.E. Barón

      • Abstract
      • Slides

      Background:
      miRNAs have shown exceptional promise as biomarkers of lung cancer; however, no miRNA signatures have yet reached the clinic. Towards developing a signature with a high likelihood of being validated externally for clinical use, we screened a panel of 50 miRNAs shown to be effective biomarkers in at least two previous studies for distinguishing human lung cancer samples from non-cancer samples.

      Methods:
      Sixty tumor-normal pairs (33 adenocarcinoma, 27 squamous cell carcinoma) were used to identify the best-performing combination of 4 miRNAs for distinguishing tumor samples from normal. The miRNA levels were measured by RT-qPCR using Taqman custom-made microfluidics cards and primer pools purchased from Life Technologies. All possible combinations of 4 miRNAs were tested, and best performance was defined as the highest median area-under the receiver operating curve (AUC) obtained from 1000 bootstrap replicates. A second, independent set of 68 tumor-normal samples (half adenocarcinoma, half squamous) was used as a test set, and bootstrapping was used to determine the 95% confidence interval for the AUC.

      Results:
      The median AUC for the top-performing panel of 4 miRNAs in our training set was 0.96. Several other miRNA combinations exhibited AUCs > 0.95 as well. In our test set, the top-performing panel (and only panel tested) exhibited an AUC of 0.97 (0.93, 0.99). This panel consisted of miRs 26a, 145, 183 and 486. miRs 145 and183 have previously been shown, when used individually, to be significant lung tumor biomarkers in at least 4 previous studies; miR-486 has been replicated 8 times.Figure 1



      Conclusion:
      Consistent with previous studies, we’ve identified a panel of 4 miRNAs that shows excellent potential for diagnosing lung tumors. Each of these miRNAs has been replicated as a biomarker of lung cancer in at least two previous studies, suggesting a high likelihood of achieving clinical validation. Several previous studies have also shown that these four miRNAs are potentially useful as biomarkers for diagnosing lung cancer using blood samples, and we are currently pursuing such validation studies.

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    P3.06 - Poster Session/ Screening and Early Detection (ID 220)

    • Event: WCLC 2015
    • Type: Poster
    • Track: Screening and Early Detection
    • Presentations: 1
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      P3.06-008 - Meta-Analysis Criteria Used to Rank Biomarkers for Validation Testing: What Works? (ID 81)

      09:30 - 17:00  |  Author(s): A.E. Barón

      • Abstract
      • Slides

      Background:
      Hundreds of biomarkers are being developed for the screening and early detection of lung cancer. The vast majority, however, even after extensive internal validation, will likely fail during external validation. For biomarkers to reach the clinic, therefore, it’s imperative that external validation studies focus on the most promising candidates. Towards this end, various strategies have been proposed to rank order and prioritize biomarker candidates. These strategies range from simple, highly intuitive ideas to highly sophisticated statistical analyses. To our knowledge, however, none of these strategies has itself been validated externally, which is an important consideration given that each strategy involves making subjective decisions. Here we conducted an independent validation test to assess the performance of the “vote-counting strategy”, a straightforward, commonly used strategy that ranks biomarkers on the basis of three highly intuitive criteria: the number of supporting studies in the literature, the combined sample size in the supporting studies, and the average fold change difference associated with the biomarker.

      Methods:
      We obtained vote-counting biomarker rankings from two recent meta-analyses that together surveyed over 180 miRNAs reported to distinguish lung tumor tissue from normal. We compared the rankings of 50 top candidates and 22 unranked miRNAs to our RT-qPCR results obtained from 45 tumor-normal pairs. We tested for a statistically significant Pearson correlation (r) between biomarker performance and the rankings according to each of the three ranking criteria.

      Results:
      We found that the number of supporting studies in the literature was indeed a statistically significant predictor of biomarker performance (r = 0.44, n = 50, p = .0006). Our results also suggested that markers supported by two studies in the literature had approximately a 50% chance of being confirmed, markers supported by 3 studies about a 67% chance, and markers supported by 6 studies about a 90% chance. Our unranked markers showed only a 5% chance of being confirmed. At the same time, we found that the combined sample size in the supporting studies was not a predictor of biomarker performance (r = 0.11, n = 50, p = 0.29). We also found that the mean fold change associated with each biomarker was not a predictor (r = 0.12, n = 47, p = 0.22) because large fold-change differences were also associated with large amounts of variability between studies.

      Conclusion:
      Considering that vote counting has obvious limitations (such as selection bias, not counting negative votes, and the variation in how different studies define significance) counting the number of supporting studies in the literature appears to work remarkably well for ranking biomarker candidates. On the other hand, using total sample size or mean fold change in the supporting studies to rank biomarker candidates appears to provide little, if any, added value. Our results also indicate a need for external validation testing of the current strategies being used to rank biomarkers across studies.

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