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G.R. Simon



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    MO04 - Lung Cancer Biology I (ID 86)

    • Event: WCLC 2013
    • Type: Mini Oral Abstract Session
    • Track: Biology
    • Presentations: 1
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      MO04.06 - DISCUSSANT (ID 3894)

      16:15 - 17:45  |  Author(s): G.R. Simon

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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    O04 - Molecular Pathology I (ID 126)

    • Event: WCLC 2013
    • Type: Oral Abstract Session
    • Track: Pathology
    • Presentations: 1
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      O04.02 - Using NGS for Mutational Profiling of NSCLC in the Clinical Setting (ID 2571)

      10:30 - 12:00  |  Author(s): G.R. Simon

      • Abstract
      • Presentation
      • Slides

      Background
      Recent advances in molecular characterization of lung cancer have led to the identification of potential therapeutic targets that play key roles in regulating cell growth and proliferation. With the introduction of new targeted therapies, it becomes increasingly important to accurately characterize mutation status in lung cancer patients to provide personalized care that define prognosis and predict response to therapy. The advent of next generation sequencing (NGS) platforms in the realm of clinical molecular diagnostics has made multi-gene mutational profiling an affordable and highly successful methodology for massively parallel sequencing using small quantities of DNA.

      Methods
      Tumor specimens from 262 distinct samples of primary lung carcinoma including adenocarcinoma (n=228), squamous cell carcinoma (n=15), non small cell cancer not otherwise specified (NSC-NOS) (n=8), poorly differentiated carcinoma (n=4), neuroendocrine carcinoma (n=2), small cell carcinoma (n=1) and pleomorphic carcinoma (n=4) were tested by NGS. Tumor samples included formalin-fixed paraffin-embedded surgical core needle biopsies, resection specimens, cytopathology cell blocks, as well as cytopathology direct smears. Ten ng of DNA from each sample was tested for mutations in hotspot regions of 46 cancer related genes (Ion AmpliSeq Cancer Panel) using either a 316 chip or a 318 chip on an Ion Torrent Personal Genome Machine (PGM) Sequencer (Life Technologies, CA).

      Results
      Mutations were detected in 222/240 (93%) patients with a histologic diagnosis of adenocarcinoma, NSC-NOS or PDC. EGFR mutations were detected in 47 (20%) of these patients and double EGFR mutations identified in 13 cases, including acquired resistance mutations T790M (n=6) and S768I (n=3). KRAS mutations were detected in 61 (25%) cases, most commonly involving codons 12 and 13 (n= 58) and less frequently involving codons 61 and 146 (n= 3). TP53 was most frequently mutated (n=65; 27%) and was often seen in conjunction with EGFR mutations (n=14; 5%) and KRAS mutations (n=15; 6%). Mutations were detected in 10/15 (67%) squamous cell carcinomas with mutations in TP53 (n=5), CDKN2A (n=3) and PIK3CA (n=2) most frequently seen. Additional mutations detected at a lower frequency from the entire dataset were STK11, ATM, BRAF, PIK3CA, CTNNB1, IDH1, NRAS, CDKN2A, KDR, RET, MET, FBXW7, APC, RB1, FLT3, GNAS, ABL1, HRAS, PTPN11, JAK3, NOTCH1, SMAD4, SMARCB1, SMO, MLH1, AKT1, and ERBB4.

      Conclusion
      In summary, our results show that NGS-based mutational profiling using small amounts of DNA derived from FFPE as well as cytology smears can provide important information regarding mutation status of genes that play key roles in growth and progression of tumor in lung cancer patients and can provide insight into directing personalized cancer therapy.

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    P1.18 - Poster Session 1 - Pathology (ID 175)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Pathology
    • Presentations: 1
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      P1.18-012 - Thyroid transcription factor (TTF-1) negative lung adenocarcinomas will be wild type for epidermal growth factor receptor (EGFR) mutations. (ID 2036)

      09:30 - 16:30  |  Author(s): G.R. Simon

      • Abstract

      Background
      TTF-1 is expressed in approximately 70% of adenocarcinomas (ACs) of the lung. EGFR mutations are present in 13-15% of unselected patients with AC in the United States and national guidelines suggest initiating first line EGFR tyrosine kinase inhibitors in this population. Both high TTF1 expression and EGFR mutations are associated with terminal respiratory unit (TRU) type ACs, female sex, never-smoking status and longer survival. We hypothesized that TTF-1 negative AC would have a high probability of being negative for EGFR mutations.

      Methods
      Microdissected formalin-fixed paraffin-embedded tumors from 693 patients with NSCLC were analyzed for EGFR mutations by allele-specific PCR in a pilot data set to test the hypothesis (pilot cohort). TTF-1 status was documented as positive, negative or not reported. Negative predictive value (NPV) for a range of true prevalences of EGFR mutation (1%-50%) was estimated using a Bayesian modeling approach. To further corroborate the hypothesis, a separate validation cohort of patients treated with erlotinib at two academic affiliated institutions with known TTF1 and EGFR mutation status was studied using the same modeling approach (validation cohort).

      Results
      301 patients with documented ACs and known TTF-1 status were included in the pilot cohort. In this population enriched to have EGFR mutations, EGFR mutations were present in 224 specimens (74%). Only 2 of the 224 specimens that were positive for EGFR mutations were negative for TTF-1 expression yielding a sensitivity of 99.1% (95% confidence interval (CI) 96.8-99.9%). For prevalence rates of EGFR mutations of 13% and 15%, the estimated NPV are 99.5% (95% credible interval (CRI) 98.6%-99.9%) and 99.4% (98.4%-99.9%), respectively. Data from 211 patients comprised the validation cohort. With an 11% rate of EGFR mutations, the estimated NPV was 92% (95% CRI - 73%-99%). For true EGFR mutation rates of 13% and 15%, using the data from the validation cohort, the estimated NPVs were 97% (95% CRI 92%-99%) and 96% (95% CRI 91%-99%), respectively. Figure 1. estimated NPVby true prevalence of EGFR mutation for both datasets Figure 1

      Conclusion
      An overwhelming majority of Lung ACs that are TTF-1 negative will be negative for EGFR mutations. These findings may be useful in avoiding delay of chemotherapy initiation in TTF-1 negative patients with newly diagnosed non-small cell lung cancer.

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    P2.11 - Poster Session 2 - NSCLC Novel Therapies (ID 209)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Medical Oncology
    • Presentations: 1
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      P2.11-046 - A Novel Approach to Increase the Efficiency of Survival-Endpoint<br /> Phase II Trials. (ID 3153)

      09:30 - 16:30  |  Author(s): G.R. Simon

      • Abstract

      Background
      Lung cancer is the second most common cancer in United States. However, new molecular information whether arising from identification of key mutations, or Next Gen Sequencing (NGS) has lead to the fragmentation of this common disease into multiple and often very rare molecular subtypes. Even though this has enabled us to substantially improve survival in specific molecular subtypes with targeted agents, having sufficient numbers of patients to demonstrate the effectiveness of novel targeted therapies for each subtype has therefore become challenging, essentially impeding progress.

      Methods
      Use of sample size determination software allows for comparison of phase II trials with a target survival proportion at a given time T based upon Kaplan-Meier (KM) versus exponential (E) survival methods. This comparison was made in instances where the exponential distribution assumption is valid.

      Results
      The use of exponential survival fitting methods, in lieu of the currently implemented KM trial designs, to single arm phase II studies can routinely reduce patient numbers by 25-40% (Table) without compromising the statistical power. Another substantial advantage is that the variability in the survival information for the exponential fit estimate both before and after the median survival points is reduced. Since patient accrual is staggered ,this reduced variability allows for obtaining robust survival information with shorter follow up times T. Any additional follow-up beyond T only further improves the E estimate, but not the KM estimate. Thus, compared to the KM approach, the E approach will allow us to do single arm phase II trials with smaller numbers of patients without compromising statistical power. Robust survival estimates can also be achieved with shorter follow up periods. Figure 1

      Conclusion
      When conducting single arm phase II clinical trials with rare molecular entities of lung cancer, the exponential survival fitting method could replace the current standard approach. Robust survival information can be obtained with smaller numbers of patients and with shorter survival times. Detailed examples and analysis will be presented.