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R. McKenna

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    ORAL 13 - Immunotherapy Biomarkers (ID 104)

    • Event: WCLC 2015
    • Type: Oral Session
    • Track: Biology, Pathology, and Molecular Testing
    • Presentations: 1
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      ORAL13.02 - Characterization of PD-L1 Expression Related to Unique Genes in NSCLC Tissue Samples (ID 2173)

      16:45 - 18:15  |  Author(s): R. McKenna

      • Abstract
      • Presentation
      • Slides

      Programmed cell death protein 1 (PD-1) receptors are members of the B7:CD28 family that interact with PD-1 ligands PD-L1 and PD-L2 to regulate cytotoxic T cell (CTL) tolerance (Freeman, J Exp Med. 2000; Latchman, Nat Immunol. 2001). Successful evasion of transformed cells from host defense is a feature of cancer (Hanahan, Cell 2011). Immune evasion can occur via the engagement of PD-1 with PD-L1 or PD-L2 (Dong, Nature Med 2002). In metastatic non-small cell lung cancer (NSCLC), PD-L1 expression has been associated with increased response to inhibitors of PD-1 (Garon, NEJM 2015). Current adjuvant cytotoxic approaches are associated with a real but small survival increases and significant toxicity. Characterization of PD-L1 expression in resected tumors could guide development of immune checkpoint based adjuvant trials.

      Microarray analyses were performed to assess gene expression for 320 NSCLC and 15 normal lung resection specimens profiled on the Agilent Whole Human Genome 4x44K 2-color platform. The reference sample used in the experiments was an equal mixture of 258 of the 320 NSCLC samples included in the study. Microarray data was imported into Rosetta Resolver for analysis. The Rosetta Similarity Tool (ROAST) was utilized to find genes correlated to PD-L1 expression. Both PD-L1 and the target gene had to be differentially expressed for sample to be included in computation of correlation. Cosine correlation was used as the similarity metric. Functional genomic analysis on the list of PD-L1 correlated genes was performed using tools available with the DAVID Bioinformatics resources ( Survival analyses based on PD-L1 expression were performed using the Kaplan-Meier method and compared using the log-rank test. Samples with PD-L1 log(ratio) > 0 and p-value < 0.01 were classified as upregulated, samples with p-value>0.01 were classified as unchanged, and sample with log(ratio) < 0 and p-value <0.01 were classified as downregulated.

      The reference level of PD-L1 expression among the subset of normal lung and NSCLC tissue samples was higher compared to levels seen in 503 breast cancer and 149 endometrial cancer tissue samples. Within the 320 NSCLC tissue samples, 174 unique genes are highly correlated with PD-L1 expression (r range= 0.692-0.904). 80 tissue samples (25%) had a PD-L1 log ratio > 0, and 63 tissue samples had large sets of highly correlated genes, a similar prevalence to membranous staining in half the cells in metastatic NSCLC (Garon, NEJM 2015). Functional analyses revealed that the genes significantly correlated with PD-L1 expression were involved in immune and inflammatory response. No significant difference in overall survival was noted (p=.661), but increased PD-L1 expression was clearly not associated with better outcomes.

      Within the NSCLC cohort, there is a group of patients with high expression for PD-L1 and related genes. This group does not have a better prognosis in comparison to those with typical or decreased PD-L1 expression. Due to the relationship between PD-L1 expression and response to anti-PD-1 therapy in metastatic NSCLC, this data and its correlation with other clinical characteristics of the patients can guide the design of adjuvant approaches based on immune checkpoint inhibitors.

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