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C.J. Rivard



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    MA15 - Immunotherapy Prediction (ID 400)

    • Event: WCLC 2016
    • Type: Mini Oral Session
    • Track: Chemotherapy/Targeted Therapy/Immunotherapy
    • Presentations: 1
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      MA15.11 - Acquired Resistance Mechanisms to EGFR Kinase Inhibitors Alter PD-L1 Expression Status in Lung Cancer (ID 4652)

      14:20 - 15:50  |  Author(s): C.J. Rivard

      • Abstract
      • Slides

      Background:
      Immunotherapies that target PD-1/PD-L1 exploit the primary roles of cytotoxic agents in lung cancers. However, tyrosine kinase inhibitors (TKIs) are still considered to be the first choice in lung cancer patients with EGFR mutations. Although immunotherapies may be applied as second line or later therapeutic approaches in these patients, after acquisition of resistance to EGFR-TKIs, it is unclear if acquired resistance mechanisms alter PD-L1 expression status that is employed as an important predictive biomarker for PD-1/PD-L1 targeting agents.

      Methods:
      Lung cancer cell lines with EGFR mutations (HCC827, HCC4006, PC9, and H1975) and their isogenic descendants with acquired resistance to various EGFR-TKIs were examined in this study. The resistance mechanisms of descendants include T790M secondary mutation, MET gene amplification, epithelial to mesenchymal transition (EMT), and loss of amplified EGFR mutant allele. PD-L1 expression status was analyzed by immunohistochemistry (IHC) and immunoblotting. Effects of acquired resistance mechanisms on PD-L1 expression were also evaluated by shRNA mediated knockdown of candidate molecules, and co-localization analysis using fluorescent imaging. IFN-gamma was used to mimic immune cell attack. Published microarray data of cells with acquired resistance to EGFR-TKIs were also employed to evaluate our findings.

      Results:
      PD-L1 expression was upregulated in several resistant cells and correlated with EGFR activation. In addition, we found that the phosphorylation of EGFR tyrosine (Y) 992 site, but not Y845, Y1068, or Y1173, was correlated with increased expression of PD-L1. We also observed that TKI-resistant cells with marked E-cadherin downregulation (HCC4006 erlotinib resistant cells and H1975 osimertinib resistant cells), one of hallmarks of EMT, showed decreased expression of PD-L1. However, one cell line (853#10), displaying EMT-like phenotype but only slight E-cadherin downregulation, showed PD-L1 upregulation. Published microarray data from three TKI-resistant lines with EMT-like features also support the correlation of low E-cadherin and reduced PD-L1 expression. ShRNA mediated knockdown of E-cadherin decreased the expression of PD-L1 in parental cell lines. IFN-gamma treatment upregulated PD-L1 expression in both parental and in resistant cells with E-cadherin downregulation, however PD-L1 expression in resistant cells was still lower and localized mainly in the cytoplasm rather than the cell membrane.

      Conclusion:
      We observed a dramatic change of PD-L1 expression status in lung cancers with EGFR mutation after acquisition of resistance to EGFR-TKIs, depending on the resistance mechanisms. These results support the importance of re-biopsy after acquisition of resistance to EGFR-TKIs, not only for the resistance mechanisms but also for the evaluation of PD-L1 expression status.

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    OA19 - Translational Research in Early Stage NSCLC (ID 402)

    • Event: WCLC 2016
    • Type: Oral Session
    • Track: Early Stage NSCLC
    • Presentations: 1
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      OA19.01 - A Standardized and Validation of Prognostic Gene Expression Signatures for Squamous Cell Lung Carcinoma by the SPECS Lung Consortium (ID 4329)

      11:00 - 12:30  |  Author(s): C.J. Rivard

      • Abstract
      • Presentation
      • Slides

      Background:
      High-throughput gene expression profiling led to proposal of multiple expression-based prognostic signatures for squamous cell lung carcinoma (SCC), but none has been validated. A multi-institutional squamous lung cancer consortium of investigators is developing prognostic signatures through the US NCI Lung SPECS (Strategic Partnership for Evaluation of Cancer Signatures) program. Six institutions contributed tumor specimens and published/unpublished expression-based prognostic signatures for validation using standardized sample cohorts (a primary validation cohort comprising institutional cases, and additional validation cohorts from two prospective cooperative group studies) and quality controlled assessment in independent laboratory and statistical cores. Here, we report the results of the primary validation.

      Methods:
      Cases of primary SCC (by central pathology review) meeting clinical (Stage I-II; surgical treatment only; 3-year followup) and specimen quality criteria (Tumor cellularity >= 50%; necrosis <= 20%) were submitted. Clinical, pathological and outcome data were uploaded to a central database. Frozen tumor samples underwent centralized mRNA extraction (Qiagen Symphony), quality control (RIN >= 6.0) and microarray profiling (Affymetrix U133) in core labs. An independent statistical core assessed validation of 7 pre-existing mRNA signatures and generated new models using MCP clustering.

      Results:
      Among 250 cases meeting entry criteria, median age was 70 (43-92), 161 (65%) were male, and most were former (70%) or current (28%) smokers. Surgery was pneumonectomy: 5%; bilobectomy: 2%; lobectomy: 74%; sublobar: 18%. Pathologic staging was T1: 49%; T2: 50%; T3: 1%; N0: 88%; N1: 12%, and grade was G1: 4%; G2: 50%; G3: 44%. At followup, 148 (59%) were deceased. Three mRNA signatures demonstrated significant univariable association with OS and added independent prognostic value (see Figure) to a multivariable model accounting for age, sex and stage (c-index = 0.641).

      Conclusion:
      The validated signatures, along with two novel signatures generated from the current dataset, are currently undergoing further validation studies using two prospective co-operative group cohorts. Figure 1



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    P1.05 - Poster Session with Presenters Present (ID 457)

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Early Stage NSCLC
    • Presentations: 2
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      P1.05-001 - Creation and Early Validation of Prognostic miRNA Signatures for Squamous Cell Lung Carcinoma by the SPECS Lung Consortium (ID 6088)

      14:30 - 15:45  |  Author(s): C.J. Rivard

      • Abstract

      Background:
      Despite overall favorable prognosis for operable early stage non-small cell lung cancer, predicting outcome for individual patients has remained challenging. Small retrospective studies have reported potential non-coding micro(mi)RNAs that might have prognostic significance; however, these studies lacked statistical power and validation. To refine these initial findings to clinical application, the investigators have undertaken a collaborative, structured evaluation of multiple signatures putatively prognostic for lung squamous cell carcinoma (SCC) under a NCI/SPECS (Strategic Partnerships fo Evaluating Cancer Signatures) award. The study design specifies a primary validation cohort comprising institutional cases, and additional validation cohorts of Cooperative Group cases, all profiled via a common pipeline.

      Methods:
      Completely resected SCC (confirmed by central pathology review) meeting clinical (Stage I-II; complete 3-year follow-up) and specimen quality criteria (Tumor cellularity ≥ 50%;necrosis ≤ 20%) were submitted by 6 institutions. Clinical, pathological and outcome data were uploaded to a central database. Lysates from 5 um sections of FFPE SSC tumor samples were run on the HTG EdgeSeq Processor (HTG Molecular Diagnostics, Tucson, AZ) using the miRNA whole transcriptome assay in which an excess of nuclease protection probes (NPPs) complimentary to each miRNA hybridize to their target. S1 nuclease then removes un-hybridized probes and RNA leaving behind only NPPs hybridized to their targets in a 1-to-1 ratio. Samples were individually barcoded (using a 16-cycle PCR reaction to add adapters and molecular barcodes), individually purified using AMPure XP beads (Beckman Coulter, Brea, CA) and quantitated using a KAPA Library Quantification kit (KAPA Biosystems, Wilmington, MA). Libraries were sequenced on the Illumina HiSeq platform (Illumina, San Diego, CA) for quantification. Standardization and normalization was provided to the project statistical core for validation of two pre-existing signatures and generation of new models (MCP clustering).

      Results:
      Among 224 cases with miRNA data, median age was 70 (43-92), 143 (64%) male, with 67% former (67%) and current (26%) smokers. All patients were completely resected stage I or II. . At follow-up, 59 (26%) had documented recurrence and 129 (58%) were deceased. To date, we have been unable to validate the previous models, but have created a novel signature of three miRNAs (see Figure) that is being validated in the second phase of the project using an independent, blinded multi-institutional cohort.

      Conclusion:
      The Squamous Lung Cancer SPECS Consortium has established well-annotated and quality-controlled resources for validation of prognostic miRNA signatures. A new candidate 3-miRNA signature has been identified for further development as a clinically useful biomarker.

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      P1.05-027 - Novel Prognostic Gene Expression Signatures for Squamous Cell Lung Carcinoma: A Study by the SPECS Lung Consortium (ID 4490)

      14:30 - 15:45  |  Author(s): C.J. Rivard

      • Abstract

      Background:
      A multi-institutional squamous lung cancer consortium of investigators is developing prognostic signatures through the US NCI Lung SPECS (Strategic Partnership for Evaluation of Cancer Signatures) program. Six institutions contributed tumor specimens and published/unpublished expression-based prognostic signatures for validation using standardized sample cohorts (a primary validation cohort comprising institutional cases, and additional validation cohorts from two prospective cooperative group studies) and quality controlled assessment in independent laboratory and statistical cores. Here, we report on de novo prognostic signatures derived using the pooled institutional dataset.

      Methods:
      Highly quality-controlled cases of primary SCC from the pooled cohort (N=249) were analyzed to generate de novo prognostic signatures from among the 147 genes comprising pre-existing signatures, and from among all profiled genes. Minimax Concave Penalty (MCP) selection and Ward’s minimum variance clustering yielded survival analyses with 2 clusters that were evaluated using Cox regression and bootstrap cross validation (bCV; 500 iterations).

      Results:
      Two significantly prognostic models were generated (see Figure): Pooled Model A (PMA) was the optimal 2-cluster model using probesets representing 6 genes selected from components of pre-existing signatures: CASP8, MDM2, SEL1L3, RILPL1, LRR1, COPZ2. Pooled Model B (PMB) was the optimal 2-cluster model using probesets representing 6 genes selected from among all those profiled: SSX1, DIAPH3, LOC619427, CASP8, EIF2S1, HSPA13. PMA and PMB each remained independently prognostic in multivariable analyses incorporating an a priori baseline model (age, sex, stage; c-index = 0.641).

      Conclusion:
      Two de novo prognostic signatures were derived using a pooled multi-institutional cohort of SCC assembled for validation of pre-existing signatures. PMA and PMB were each found to be independently prognostic, accounting for established clinical predictors. Both now move forward, along with validated pre-existing signatures, to additional assessment of discrimination, calibration and clinical usefulness using additional independent prospective US co-operative group cohorts of cases. Figure 1



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    P2.03b - Poster Session with Presenters Present (ID 465)

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Advanced NSCLC
    • Presentations: 1
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      P2.03b-035 - EGFR FISH as Potential Predictor of Necitumumab Benefit with Chemotherapy in Squamous NSCLC: Subgroup Analyses from SQUIRE (ID 5708)

      14:30 - 15:45  |  Author(s): C.J. Rivard

      • Abstract

      Background:
      Necitumumab (Neci) is a monoclonal antibody directed against the human epidermal growth factor receptor (EGFR). In the SQUIRE trial (NCT00981058), the addition of Neci to gemcitabine plus cisplatin (Gem-Cis) in squamous cell lung cancer resulted in a significant advantage in terms of overall survival (OS), but the expression of EGFR assessed by immunohistochemistry was not able to robustly predict the benefit from Neci. In a post-hoc analysis of SQUIRE, EGFR gene copy number gain determined by fluorescence in situ hybridization (FISH) showed a trend towards improved OS (HR=0.70) and progression-free survival (PFS) (HR=0.71) with the addition of Neci. We present the analysis of granular EGFR-FISH data from SQUIRE to examine the potential predictive role of high polysomy (HP) vs gene amplification (GA) as both were included in the “FISH-positive” category.

      Methods:
      Suitable specimens from SQUIRE patients underwent FISH analysis. Probe hybridization was performed in a central laboratory and each sample was analyzed using the Colorado EGFR scoring criteria. FISH was considered positive in cases of HP (≥40% cells with ≥4 EGFR copies) or GA (EGFR/CEP7 ≥2 or ≥10% cells with ≥15 EGFR copies). The correlation of granular FISH parameters with clinical outcomes was assessed.

      Results:
      FISH analysis was available for 557 patients (out of 1093); 208 patients (37.3%) were FISH+, including 167 (30.0%) with HP and 41 (7.4%) with GA. The outcome data for HP and GA are reported below:

      HIGH POLYSOMY GENE AMPLIFICATION
      Neci+Gem-Cis (N=89) Gem-Cis (N=78) Neci+Gem-Cis (N=22) Gem-Cis (N=19)
      Median OS in months (95% CI) 12.58 (11.04-16.00) 9.53 (7.16-12.48) 14.78 (10.02-31.51) 7.62 (4.99-16.10)
      Hazard ratio within subgroup (interaction model) 0.77 (0.55-1.08) p = 0.133 0.45 (0.21-0.93) p = 0.033
      Interaction p value 0.189
      Median PFS in months(95% CI) 6.08 (5.59-7.59) 5.13 (4.24-5.72) 7.36 (4.27-11.40) 5.55 (2.79-8.34)
      Hazard ratio within subgroup (interaction model) 0.70 (0.50-0.99) p = 0.044 0.69 (0.33-1.45) p = 0.334
      Interaction p value 0.980


      Conclusion:
      The OS benefit from the addition of Neci to Gem-Cis appeared to be more pronounced in the small subset of patients with GA when compared to HP, but the same trend was not observed for PFS. The potential predictive value of different EGFR FISH parameters should be evaluated in future studies.