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K. Ellison



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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
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      ORAL25.06 - Association of Expression of PD-L1 with the Tumor Immune Microenvironment in Small Cell Lung Cancer (ID 859)

      10:45 - 12:15  |  Author(s): K. Ellison

      • Abstract
      • Presentation
      • Slides

      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
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      ORAL37.07 - Lung Cancer Mutation Consortium Pathologist Panel Evaluation of MET Protein (ID 2129)

      16:45 - 18:15  |  Author(s): K. Ellison

      • Abstract
      • Presentation
      • Slides

      Background:
      MET is a receptor tyrosine kinase with frequently activated signaling in lung cancers. Multiple studies indicate that MET overexpression correlates with poor clinical prognosis. Tumors with MET amplification and overexpression may respond better to MET inhibitors than tumors with low expression. The prevalence of MET overexpression in lung cancer cohorts has varied from 20%-80%, as has the proportion of patient’s testing positive for prospective clinical trials with entry based on MET overexpression. The Lung Cancer Mutation Consortium (LCMC) Pathologist Panel endeavored to standardize evaluation of MET protein expression with “Round Robin” conferences.

      Methods:
      508 FFPE non-small cell lung cancer specimens were stained by immunohistochemistry for MET protein expression (SP44 antibody, Ventana). Seven pathologists from LCMC sites with specialized training in MET scoring evaluated 78 Aperio-scanned images of MET-stained slides in two successive rounds of 39 different cases per round. The percentage of tumor cells with membranous and/or cytoplasmic staining at different intensities were evaluated with H-scores ranging from 0 to 300. Overall group and individual pathologist’s scores were compared with intraclass correlation coefficients (ICCs). Between rounds, a “Round Robin” teleconference was conducted to review discordant cases and improve consistency of scoring. Steps to improve scoring included: review of a Roche MET training document, sharing pictures of cases with concordant scores (Figure 1), and provision of H&E images for the second round to facilitate identification of tumor areas. Figure 1



      Results:
      The overall average MET H-score for the 78 cases was 165.3 (H-score range: 42.5-279.7). The average H-score was <125 for 14 specimens, 125-175 for 35 specimens, and >175 for 29 specimens. The overall group ICC comparing the consistency of H-scores from all 7 pathologists improved from 0.50 (95% confidence interval: 0.37-0.64, “fair” correlation) for the first scoring round to 0.74 (95% confidence interval: 0.64-0.83, “good” correlation) for the second round. A comparison of the individual pathologist’s ICCs demonstrated improved individual scoring consistency for all seven pathologists between rounds with an average of 0.64 (“moderate” correlation, range 0.43-0.76) for the first round and 0.82 (“almost perfect” correlation, range 0.75-0.93) for the second round.

      Conclusion:
      Development of standardized, reproducible strategies for evaluation of complex biomarkers, such as MET, are critical to clinical trial design. The consistency of scoring for MET protein expression and other biomarkers may be improved by continuous training and communication between pathologists with easy access to H&E images and other visual aids.

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