Browsing by Author "Su, Jen-Liang"

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NF-kappa B-driven suppression of FOXO3a contributes to EGFR mutation-independent gefitinib resistance
(2016-05-03)
Chiu, Ching-Feng
;
Chang, Yi-Wen
;
Kuo, Kuang-Tai
;
Shen, Yu-Shiuan
;
Liu, Chien-Ying
Therapy with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (EGFR-TKIs, such as gefitinib or erlotinib) significantly prolongs survival time for patients with tumors harboring an activated mutation on EGFR; however, up to 40% of lung cancer patients exhibit acquired resistance to EGFR-TKIs with an unknown mechanism. FOXO3a, a transcription factor of the forkhead family, triggers apoptosis, but the mechanistic details involved in EGFR-TKI resistance and cancer stemness remain largely unclear. Here, we observed that a high level of FOXO3a was correlated with EGFR mutation-independent EGFR-TKI sensitivity, the suppression of cancer stemness, and better progression-free survival in lung cancer patients. The suppression of FOXO3a obviously increased gefitinib resistance and enhanced the stem-like properties of lung cancer cells; consistent overexpression of FOXO3a in gefitinib-resistant lung cancer cells reduced these effects. Moreover, we identified that miR-155 targeted the 3\'UTR of FOXO3a and was transcriptionally regulated by NF-kappa B, leading to repressed FOXO3a expression and increased gefitinib resistance, as well as enhanced cancer stemness of lung cancer in vitro and in vivo. Our findings indicate that FOXO3a is a significant factor in EGFR mutation-independent gefitinib resistance and the stemness of lung cancer, and suggest that targeting the NF-kappa B/miR-155/FOXO3a pathway has potential therapeutic value in lung cancer with the acquisition of resistance to EGFR-TKIs.
Triple-layer dissection of the lung adenocarcinoma transcriptome - regulation at the gene, transcript, and exon levels
(2015-10-06)
Hsu, Min-Kung
;
Wu, I-Ching
;
Cheng, Ching-Chia
;
Su, Jen-Liang
;
Hsieh, Chang-Huain
Lung adenocarcinoma is one of the most deadly human diseases. However, the molecular mechanisms underlying this disease, particularly RNA splicing, have remained underexplored. Here, we report a triple-level (gene-, transcript-, and exon-level) analysis of lung adenocarcinoma transcriptomes from 77 paired tumor and normal tissues, as well as an analysis pipeline to overcome genetic variability for accurate differentiation between tumor and normal tissues. We report three major results. First, more than 5,000 differentially expressed transcripts/exonic regions occur repeatedly in lung adenocarcinoma patients. These transcripts/exonic regions are enriched in nicotine metabolism and ribosomal functions in addition to the pathways enriched for differentially expressed genes (cell cycle, extracellular matrix receptor interaction, and axon guidance). Second, classification models based on rationally selected transcripts or exonic regions can reach accuracies of 0.93 to 1.00 in differentiating tumor from normal tissues. Of the 28 selected exonic regions, 26 regions correspond to alternative exons located in such regulators as tumor suppressor (GDF10), signal receptor (LYVE1), vascular-specific regulator (RASIP1), ubiquitination mediator (RNF5), and transcriptional repressor (TRIM27). Third, classification systems based on 13 to 14 differentially expressed genes yield accuracies near 100%. Genes selected by both detection methods include C16orf59, DAP3, ETV4, GABARAPL1, PPAR, RADIL, RSPO1, SERTM1, SRPK1, ST6GALNAC6, and TNXB. Our findings imply a multilayered lung adenocarcinoma regulome in which transcript-/exon-level regulation may be dissociated from gene-level regulation. Our described method may be used to identify potentially important genes/transcripts/exonic regions for the tumorigenesis of lung adenocarcinoma and to construct accurate tumor vs. normal classification systems for this disease.