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MINI 34 - RNA and miRNA (ID 162)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
MINI34.11 - Identification and Functional Characterization of Non-Small Cell Lung Cancer-Associated Splice Variants and Splicing Factors (ID 2101)
18:30 - 20:00 | Author(s): R. Pio
Deregulation of alternative splicing has become a hallmark of cancer. In non-small cell lung cancer (NSCLC), the biological importance of splicing is evidenced by the identification of aberrant RNA transcripts associated with somatic mutations in genes encoding splicing factors. We have previously developed ExonPointer, an algorithm optimized to detect differential splicing cassette events from data obtained in microarrays containing probes in exons and junctions. Our present objective was to apply this technology for the identification and characterization of cancer-associated splice variants and splicing factors in NSCLC.
We applied ExonPointer for the identification of differential splice forms in lung cancer tissues (8 adenocarcinomas, 13 squamous cell carcinomas and 1 large cell carcinoma) and matched normal lung. We validated the events by RT-PCR and used bioinformatics tools, such as DAVID and Ingenuity Pathway Analysis, for cluster enrichment analyses. siRNA knockdown of specific splice isoforms was used for functional analyses. Prognostic studies were performed by immunohistochemistry in 127 primary tissues from patients with NSCLC.
The validation rate for the top 20 differentially expressed splice events identified by ExonPointer was 70%. Gene cluster analyses using the first 250 events showed a significant enrichment of cancer-related clusters such as Cellular Growth and Proliferation, or Cell Death and Survival. Among the validated genes, we identified Extended synaptotagmin-2 (ESYT2). ESYT2 is a membrane protein that mediates fibroblast growth factor receptor-1 (FGFR1) endocytosis and actin dynamics. A significantly different pattern of ESYT2 alternative splicing was found in primary lung tumors as compared to normal lung tissue (p<0.001). In particular, an isoform containing an extra exon was overexpressed in cancer tissues, while the expression of the canonical isoform was decreased. We found a significant correlation between the splicing pattern of ESYT2 and the expression of FGFR1 in a panel of 43 lung cancer cell lines (r=-0.724, p<0.001). Using siRNA downregulation, we analyzed the implication of the ESYT2 isoforms in tumor biology and demonstrated a distinct role of the splice isoforms in actin and tubulin cytoskeleton organization. We also searched for splicing factors responsible for the splicing of ESYT2. We found that the ratio of ESYT2 isoforms correlated with the expression of the splicing factor QKI in lung cancer cell lines (r=-0.793, p<0.001). Moreover, in vitro downregulation of QKI markedly affected ESYT2 splicing. Interestingly, we found a significant enrichment of QKI targets in the list of differentially spliced genes identified by ExonPointer (p<0.001), suggesting that this factor is a critical regulator of splicing in lung cancer. Finally, we observed a significant downregulation of QKI expression in primary NSCLC compared to adjacent normal lung cancer cells (p<0.001), and an association between the nuclear expression of this factor and disease-free survival (HR=0.61; 95%CI=0.35-1.05) or overall survival (HR=0.44; 95%CI=0.21-0.94).
Using a novel analytical tool we have identified new splicing variants with functional relevance in lung cancer. Moreover, changes in splicing events in lung primary tumors were found to be largely regulated by the splicing factor QKI, a potential tumor suppressor gene downregulated in NSCLC and associated with the prognosis of the disease.
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MS 02 - Are Non-Tissue Biomarkers Ready for the Clinic? (Presentation recordings currently in editing process) (ID 20)
- Event: WCLC 2015
- Type: Mini Symposium
- Track: Screening and Early Detection
- Presentations: 1
MS02.03 - Blood-Based Proteomics Strategies for the Early Detection of Lung Cancer (ID 1854)
14:15 - 15:45 | Author(s): R. Pio
Blood-based proteomics strategies for the early detection of lung cancer. Since the advent of the new proteomics era, large-scale studies of protein profiling have been exploited to identify the distinctive molecular signatures in a wide array of biological systems spanning areas of basic biological research, various disease states, and biomarker discovery directed toward diagnostic and therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomics approaches, leading to enhancement of the depth and breadth of proteome coverage. Proteomic signatures specific for invasive lung cancer and preinvasive lesions have begun to emerge. In this presentation, we will provide a critical assessment of the state of recent advances in proteomic approaches to the discovery and validation of blood based biomarker signatures for the early detection of lung cancer. Mass spectrometry and immuno-based detection methods will be reviewed including commercially available blood tests to aid the early detection of lung cancer. Much of this progress was driven by increasing knowledge of tumor-related aberrations that affect nucleic acids at genomic, transcriptional, and posttranscriptional levels. Proteins are the functional end product of genes that ultimately control vital biological processes via their expression level and posttranslational modifications. Moreover, the number of proteins produced by cells far exceeds the number of genes because proteins vary in their stability compared with mRNA and are subjected to many levels of posttranscriptional and posttranslational regulations, such as splicing variants, fusions, and posttranslational modifications. Therefore, to advance our understanding of the biology of lung cancer and to obtain a more integrated view of the disease biology, it is critical to capture the full spectrum of the variations in protein expression patterns, their posttranslational modifications, and their functions in cancer cells. Thus, we hope to take advantage of the molecular complexity of the proteome to improve early detection strategies for lung cancer. Proteomic analysis of blood represents an appealing choice to researchers addressing the discovery of biomarkers because it can be quickly and easily obtained noninvasively in large quantities over time. Several recent studies have investigated the extent to which proteomic technologies can unravel the complexity of the plasma proteome. In this regard, the Human Proteome Organization completed a comprehensive collaborative study to characterize the human serum and plasma proteomes. The rapid proteomic profiling of blood in particular has generated great enthusiasm but has been minimally successful at providing robust signatures to translate to the clinic. The major preanalytical challenges are related to the lack of standardized sample collection and preparation techniques, leading to the introduction of analytical bias and the lack of reproducibility. The extreme complexity of biofluids, such as blood, serum, or plasma, and the low abundance of most of the specific protein markers are among other factors that reduce the sensitivity of detection by proteomic technologies. After the discovery of new biomarkers, the next critical steps are to validate and evaluate their performance in clinically relevant patient populations. Multiple levels of validation have to take place before confirming the clinical utility of the biomarker. This includes confirmation of detected changes in protein level by different techniques and correlation with biological outcomes of lung cancer such as early detection, chemosensitivity, or survival. These phases of clinical validation will evaluate a biomarker's performance in relevant clinical context and how it may affect clinical management of risk or disease. Selected readings: 1. Zeng GQ, Zhang PF, Deng X, Yu FL, Li C, Xu Y, Yi H, Li MY, Hu R, Zuo JH, et al. Identification of candidate biomarkers for early detection of human lung squamous cell cancer by quantitative proteomics. Molecular & cellular proteomics : MCP. 2012;11(6):M111 013946. 2. Massion PP, and Walker RC. Indeterminate pulmonary nodules: risk for having or for developing lung cancer? Cancer Prev Res (Phila). 2014;7(12):1173-8. 3. Hassanein M, Callison JC, Callaway-Lane C, Aldrich MC, Grogan EL, and Massion PP. The state of molecular biomarkers for the early detection of lung cancer. Cancer Prev Res (Phila). 2012;5(8):992-1006. 4. Kikuchi T, Hassanein M, Amann JM, Liu Q, Slebos RJ, Rahman SM, Kaufman JM, Zhang X, Hoeksema MD, Harris BK, et al. In-depth proteomic analysis of nonsmall cell lung cancer to discover molecular targets and candidate biomarkers. Molecular & cellular proteomics : MCP. 2012;11(10):916-32. 5. Skates SJ, Gillette MA, LaBaer J, Carr SA, Anderson L, Liebler DC, Ransohoff D, Rifai N, Kondratovich M, Tezak Z, et al. Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies. Journal of proteome research. 2013;12(12):5383-94. 6. Zhang B, Wang J, Wang X, Zhu J, Liu Q, Shi Z, Chambers MC, Zimmerman LJ, Shaddox KF, Kim S, et al. Proteogenomic characterization of human colon and rectal cancer. Nature. 2014;513(7518):382-7. 7. Neal JW, Gainor JF, and Shaw AT. Developing biomarker-specific end points in lung cancer clinical trials. Nature reviews Clinical oncology. 2015;12(3):135-46.