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V. Raghavan



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    MA17 - Genetic Drivers (ID 409)

    • Event: WCLC 2016
    • Type: Mini Oral Session
    • Track: Biology/Pathology
    • Presentations: 1
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      MA17.06 - Landscape of Somatic Mutations Involving Lung Cancer Associated Genes in Non-Small Cell Lung Cancer (NSCLC) Patient-Derived Xenografts (ID 6084)

      14:20 - 15:50  |  Author(s): V. Raghavan

      • Abstract
      • Presentation
      • Slides

      Background:
      Patient-derived tumor xenografts (PDXs) have high fidelity to their histological origins, and maintain the molecular heterogeneity and genetic aberrations of the donor patient tumors more faithfully than established in non-small cell lung cancer (NSCLC) cell lines. This study evaluated whether our panel of PDX models recapitulate known cancer-related gene mutations.

      Methods:
      Whole-exome sequencing was completed on 103 NSCLC PDX models, 47 adenocarcinoma (AdC) and 56 squamous (SqCC), with a mean coverage of 84x. After filtering for contaminating mouse reads, the exome data were aligned using the Burrows-Wheeler Aligner, processed using the standard GATK pipeline, and mutations were identified using MuTect. Additional filtering using dbSNP, ExAC and ESP was performed for cases without corresponding normal adjacent lung exome data (n = 80). The identified mutations were compared to 1260 frequently mutated cancer-related genes, which were compiled from a panel of cancer-related mutated genes (555) and a panel of lung cancer-specific mutated genes (1082).

      Results:
      High rates of somatic mutations were observed in both AdC (mean of 12.4 mutations/megabase) and SqCC (mean of 11.7 mutations/megabase) PDX models. Compared to the rates observed in primary lung cancers in The Cancer Genome Atlas studies (mean of 8.9 mutations/megabase in AdC; 8.1 mutations/megabase in SqCC), these values appear higher, but may be inflated due to the lack of data from corresponding normal tissues. AdC models had a total of 953 mutated genes (median: 57 genes/model; range: 5-307), while SqCC models were characterized by 1007 mutated genes (median: 55 genes/model; range: 21-354). Specific mutation frequencies were compared to those determined in a recent study involving genomic alterations in human primary lung AdC and SqCC (Nature Genetics 2016; 48; 607–616). This comparison, based on mutated genes common in both studies, demonstrated significant correlation of the frequencies in 791 genes in AdC (ρ=0.78; p<2.2×10[-16]), as well as in 799 genes in SqCC (ρ=0.73; p<2.2×10[-16]). Three genes that were reported as significantly mutated in both AdC and SqCC primaries, and had higher mutation frequencies in SqCC, were also observed to be higher in our SqCC PDX models (TP53: 48.9% in AdC vs. 55.4% in SqCC; CDKN2A: 4.3% vs. 7.1% and PIK3CA: 2.1% vs. 23.2%); however, the statistical significance of these differences needs to be tested.

      Conclusion:
      Mutation landscapes in cancer genes are recapitulated in AdC and SqCC PDX models. The fidelity of these landscapes in matched patient primary tumour samples is being investigated.

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    P1.02 - Poster Session with Presenters Present (ID 454)

    • Event: WCLC 2016
    • Type: Poster Presenters Present
    • Track: Biology/Pathology
    • Presentations: 1
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      P1.02-036 - An EGFR Tyrosine Kinase Inhibitor Sensitive Patient-Derived Lung Cancer Xenograft Model without Classical Sensitizing Mutations (ID 5398)

      14:30 - 15:45  |  Author(s): V. Raghavan

      • Abstract

      Background:
      Mutations in the tyrosine kinase (TK) domain of EGFR are oncogenic driver in 10-20% of lung adenocarcinoma (AdC) patients in Western countries. Approximately 90% of EGFR-TK inhibitor (TKI) sensitizing mutations occur as small in-frame deletions in exon 19 or L858R point mutations in exon 21. Recently, novel driver mutations in EGFR with oncogenic and TKI sensitizing activity have been reported. We present here an AdC patient-derived xenograft (PDX) model (PDX12) that is highly sensitive to EGFR-TKI, yet failed to demonstrate classical TKI sensitizing mechanisms.

      Methods:
      Comprehensive genomics profiling was used to characterize the genotype of PDX12, which was established from a resected stage IIIA AdC patient grafted in NGS mouse. The primary human lung cancer cell line (PHLC12) was extracted from its PDX model (PDX12). Aberrant EGFR cell lines used were H3255 (L858R), H2935 (exon 19 deletion), H1975 (L858R and T790M), and H1944 (wild type). Cell viability was assessed after erlotinib treatment at 1nM - 2μM for 72 hours using MTS assay. Levels of EGFR activation in both pre- and post-treatment by Western blot analysis.

      Results:
      PDX12 model had no known oncogenic mutations (EGFR wild type) on exons 18-21 by next-generation sequencing, RT-qPCR, and SISH, but was highly sensitive to EGFR-TKI. The IC50 to erlotinib treatment at 72 hr was 67.13 ± 7.63 nM for PHLC12, compared to 9.70 ± 2.64 nM for H3255, 64.88 ± 8.49 nM for HCC2935, > 2 μM for H1975, and > 2 μM for H1944 EGFR mutant or wild type cells, respectively. Western blot analysis demonstrated a relatively higher molecular weight band for EGFR protein with high expression level in PHLC12 when compared to other lung cancer cell lines. Using RT-qPCR, relative expression level of each EGFR domain (extracellular, tyrosine kinase, and c-terminal domain) in PHLC12 showed no difference compared to EGFR wild type. Phosphorylation status of EGFR in PHLC12 was similar in activity as compared to erlotinib sensitive cell lines.

      Conclusion:
      PHLC12 represents an enigmatic EGFR TKI sensitive lung PDX model without classical TKI sensitizing aberrations. Additional potential mechanisms of EGFR dependency including exon duplication, or post-translational modification of EGFR protein are being investigated.