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S.K. Jeffus



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    P1.06 - Poster Session/ Screening and Early Detection (ID 218)

    • Event: WCLC 2015
    • Type: Poster
    • Track: Screening and Early Detection
    • Presentations: 1
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      P1.06-010 - Allelic Heterogeneity and Its Role in Identifying Non-Small Cell Lung Cancer Phenotypes (ID 2180)

      09:30 - 17:00  |  Author(s): S.K. Jeffus

      • Abstract
      • Slides

      Background:
      More people die of lung cancer (LC) annually than of prostate, colon, and breast cancers combined, making it the leading cause of cancer-related mortality in the United States. LC can be divided into two main categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NSCLC is the predominant LC category accounting for roughly 85% to 90% of all diagnosed LCs. NSCLC can be further subdivided into three main histological subtypes including adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. Phenotypic characterization (i.e. histological features and LC subtypes) for NSCLC tissues remains a difficult task. Many studies have revealed certain genes that are associated with NSCLC; however, these genes cannot completely decipher between its varying phenotypes. CD36 is a biologically plausible candidate gene that is significantly under-expressed in NSCLC tissues compared to normal tissues. This differential expression is not observed in NSCLC tissue subtypes; however, significant differences in CD36 expression have been observed in NSCLC subtype-derived cell lines. Based on this previous expression data, we hypothesized that allelic heterogeneity within CD36 exons could disparately contribute to the development of NSCLC subtypes.

      Methods:
      To test this hypothesis, we obtained fresh-frozen LC tissues from the UAMS tissue bank and performed mutation screenings using Sanger sequencing methods and Mutation Surveyor software. Quantitative RT-PCR was performed on tissue mRNA and CD36 mRNA expression was normalized to HPRT1 (a housekeeping gene that is more stable in lung tissues) expression in the same samples. Genotype-specific CD36 expressions profiles were then identified and analyzed.

      Results:
      Several previously undiscovered variants were identified in Exon 4 of the CD36 gene. Two of these variants are associated with mRNA expression differences between the variant and wild-type genotypes that identify phenotypic heterogeneity. Adenocarcinoma samples with transcript harboring the first variant genotype overexpressed CD36 mRNA as compared to adenocarcinoma samples containing the wild-type genotype (p=0.013; N=37). In squamous cell carcinoma samples, there was no significant difference between samples with the first variant and wild-type (p=0.74; N=26). Squamous cell carcinoma samples with CD36 transcript harboring the second variant genotype was relatively under-expressed when compared to the squamous cell carcinoma samples with the wild-type genotype, though the comparison only approached significance at p=0.053 (N=37). A similar comparison in adenocarcinoma samples yielded non-significant results (p=0.59; N=25).

      Conclusion:
      Identification of NSCLC phenotypes is critical to treatment, but remains difficult with current histopathological methods. Our analysis of publicly available expression data has shown that probes used in global expression microarrays cannot completely and reliably distinguish between NSCLC phenotypes at the CD36 locus. We propose that allelic heterogeneity at the CD36 locus may alter array probe binding properties leading to inconsistent expression results. Our data has identified two previously undiscovered CD36 variants that may uniquely lead to altered CD36 mRNA expressions correlating to specific NSCLC subtypes. Hence, these results suggest that we may be able to accurately quantify transcripts associated with NSCLC subtypes using allele-specific probes.

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    P3.04 - Poster Session/ Biology, Pathology, and Molecular Testing (ID 235)

    • Event: WCLC 2015
    • Type: Poster
    • Track: Biology, Pathology, and Molecular Testing
    • Presentations: 1
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      P3.04-077 - Diagnosis and Prognosis of Non-Small Cell Lung Cancer Based on Metabolic Profiles of Mediastinal Lymph Node Aspirates (ID 3050)

      09:30 - 17:00  |  Author(s): S.K. Jeffus

      • Abstract
      • Slides

      Background:
      Non-small cell lung cancer (NSCLC) has a high mortality. TNM staging has prognostic implications, but there is a paucity of biomarkers to predict prognosis. The aim of this study was to evaluate the metabolomic profiles of mediastinal and hilar lymph nodes of NSCLC patients and to determine the prognostic implications of different metabolites.

      Methods:
      Endobronchial ultrasound-guided fine needle aspirates of hilar and mediastinal nodes from patients with NSCLC were collected from January 2011 to February 2013. Metabolomic profiles were generated using liquid chromatography mass spectrometry. Electronic medical records were reviewed for histologic diagnoses and survival status. T-testing was used to compare metabolite differences between groups. Metabolites dichotomized at their median values were assessed for prognostic potential via Cox regressions. P<0.05 was regarded as statistically significant.

      Results:
      A total of 79 lymph node aspirates were collected. 50 were positive for NSCLC, 13 were negative for NSCLC in patients with biopsy-proven NSCLC at the primary site, and 16 were from patients with non-malignant lung disease. The histologic subtypes of patients with NSCLC were 38 (60.3%) adenocarcinoma (AD) and 25 (39.7%) squamous cell carcinoma (SCC). TNM staging for the patients with NSCLC was as follows: 8 (12.7%) stage I, 10 (15.9%) stage II, 23 (36.5%) III, and 22 (34.9%) IV. Concentrations of alanine, alpha-ketoglutarate, glutathione (reduced and oxidized states), homocysteine, malate, melatonin, malonyl-carnitine, S-adenosyl homocysteine, and S-adenosylmethionine were statistically significantly higher in NSCLC patients than in patients with benign disease. In contrast, citruline, cysteine, glutamine, isoleucine, L-carnitine, leucine, ornithine, tryptophan, and valine were lower in the NSCLC group than in the benign group. Metabolite concentrations were different for different cancer sub-types; SCC patients had a 4.92-fold higher concentration of succinate than AD (p<0.0001), whereas AD had a 1.52-fold higher concentration of homocysteine than SCC (p=0.041). Elevated concentrations of the following metabolites were associated with shorter overall survival: melatonin (HR=2.24, 95% CI: 1.27-3.97; p=0.0057) Figure 1, malate (HR=1.91, 95% CI: 1.08-3.35; p=0.025), cystathionine (HR=1.84, 95% CI: 1.03-3.28; p=0.039), and glutamate (HR=1.77, 95% CI: 1.01-3.09; p=0.045). Figure 1



      Conclusion:
      Metabolomic data demonstrate differences between different NSCLC subtypes. In addition, metabolomic data may have prognostic potential that is independent from that associated with TNM stage. Metabolites associated with worsened prognosis offer an avenue for research; they may allow us to identify specific pathways that correlate with prognosis.

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