MECHANISMS UNDERLYING DISTINCT EGFR VERSUS FGFR-3 AND -1 DEPENDENCY IN HUMAN BLADDER CANCER CELLS

The epidermal growth factor receptor (EGFR) and fibroblast growth factor receptor (FGFR) are activated by gene amplification, mutation and overexpression in bladder cancer, which drives tumor development and progression. Both EGFR and FGFR inhibitors are currently being tested in clinical trials. However, bladder cancer (BC) cells show remarkably heterogeneous sensitivities to both inhibitors, and the molecular determinants of this heterogeneity are presently unclear. Therefore, in this study, using selective EGFR and FGFR inhibitors in BC cells, we demonstrated that FGFR3 and FGFR1 play largely non-overlapping roles in mediating proliferation and invasion in the distinct “epithelial” and “mesenchymal” subsets of human BC cells. Furthermore, we examined the sensitivities to FGFR3 and EGFR inhibition in a panel of human BC cells, and found that FGFR3 and EGFR dependency are mutually exclusive biological phenotypes controlled by PPARγ-FABP4 pathway. This study significantly extends and complements our knowledge of molecular mechanism that mediates growth receptor dependent proliferation in BC

Climbing up the ladder of abstraction: how to span the boundaries of knowledge space in the online knowledge market?

Abstract The challenge of raising a creative question exists in recombining different categories of knowledge. However, the impact of recombination remains controversial. Drawing on the theories of knowledge recombination and category-spanning, we claim that the impact of knowledge spanning on the appeal of questions is contingent upon questions’ knowledge hierarchy in the knowledge space. Using word embedding models and network analysis to quantify knowledge spanning and knowledge hierarchy respectively, we test our hypotheses with the data collected from a large online knowledge market (N = 463,545). Knowledge spanning has an inverted U-shaped influence on the appeal of questions: the appeal of questions increases up to a threshold, after which point the positive effect reverses. However, with the increase in knowledge hierarchy, the inverted U-shape is weakened and disappears quickly. We fill the research gap by conceptualizing question-asking as knowledge-spanning and highlighting the theoretical underpinnings of knowledge hierarchy. The theoretical and practical implications for future research on knowledge recombination are discussed

Development of lactate‐related gene signature and prediction of overall survival and chemosensitivity in patients with colorectal cancer

Abstract Background Colorectal cancer (CRC) is a malignant tumor of the digestive system that contains high levels of immune cells. Lactic acid, a major metabolite, plays a crucial role in tumor development, maintenance, and therapeutic response. However, the prognostic potential and therapeutic biomarker potential of lactate‐related genes (LRGs) in CRC patients remain to be elucidated. Methods We collected the mRNA expression profile and clinical data of CRC patients from the Cancer Genome Atlas (TCGA) database and the GSE59382 cohort. Univariate Cox regression, Lasso regression and multivariate Cox regression analysis were used to construct the prognosis model. Combined with the risk score and important clinicopathological features, the nomogram was established. In addition, the relationship between risk score and immune infiltration, immune checkpoint gene expression, and drug sensitivity was investigated. Results We constructed lactate‐related gene signatures (LRGS) based on four LRGs, which independently predicted the prognosis of CRC. Patients with different risk scores are found to have distinct immune status, tumor mutation load, immune response, and drug sensitivity. In addition, nomogram results determined by risk scores and clinical factors have higher predictive performance. Conclusion We found that LRGS is a reliable biomarker for predicting clinical outcomes, evaluating immune infiltration and efficacy, and predicting the sensitivity to drugs in patients with CRC

Expression of histone deacetylase (HDAC) family members in bortezomib-refractory multiple myeloma and modulation by panobinostat

Aim: Multiple myeloma (MM) is a hematological malignancy of antibody-producing mature B cells or plasma cells. The proteasome inhibitor, bortezomib, was the first-in-class compound to be FDA approved for MM and is frequently utilized in induction therapy. However, bortezomib refractory disease is a major clinical concern, and the efficacy of the pan-histone deacetylase inhibitor (HDACi), panobinostat, in bortezomib refractory disease indicates that HDAC targeting is a viable strategy. Here, we utilized isogenic bortezomib resistant models to profile HDAC expression and define baseline and HDACi-induced expression patterns of individual HDAC family members in sensitive vs. resistant cells to better understanding the potential for targeting these enzymes.Methods: Gene expression of HDAC family members in two sets of isogenic bortezomib sensitive or resistant myeloma cell lines was examined. These cell lines were subsequently treated with HDAC inhibitors: panobinostat or vorinostat, and HDAC expression was evaluated. CRISPR/Cas9 knockdown and pharmacological inhibition of specific HDAC family members were conducted.Results: Interestingly, HDAC6 and HDAC7 were significantly upregulated and downregulated, respectively, in bortezomib-resistant cells. Panobinostat was effective at inducing cell death in these lines and modulated HDAC expression in cell lines and patient samples. Knockdown of HDAC7 inhibited cell growth while pharmacologically inhibiting HDAC6 augmented cell death by panobinostat.Conclusion: Our data revealed heterogeneous expression of individual HDACs in bortezomib sensitive vs. resistant isogenic cell lines and patient samples treated with panobinostat. Cumulatively our findings highlight distinct roles for HDAC6 and HDAC7 in regulating cell death in the context of bortezomib resistance

Relationship between FGFR/bFGF expression and EMT.

<p>A. Expression of FGFRs 1–4 and bFGF in relationship to E-cadherin expression. The relative mRNA levels were measured by quantitative real-time RT-PCR. The cell lines in each panel are organized by relative E-cadherin expression (low to high, from left to right; see Fig. 1B). B. Scatterplots depicting the relationships between FGFR1, bFGF, FGFR3, and EMT marker expression. Nonparametric correlation analyses were used to evaluate the relationships between FGFR3 and E-cadherin (CDH1) expression, FGFR1 and ZEB1 expression, bFGF and ZEB1 expression, and bFGF and FGFR1 expression. Correlation coefficients and p values are indicated on the figure.</p

Expression of FGFR1, FGFR3, and bFGF in distinct subsets of human BC cell lines.

<p>A. Correlation of FGFR1 and FGFR3 with canonical EMT markers. mRNA levels were measured using whole genome mRNA expression profiling (Illumina platform). The heat map depicts the expression of FGFR1, FGFR3, FGF2 (bFGF), p63 (TP63), E-cadherin (CDH1), Slug (SNAI2), and vimentin. B. Quantitative analysis of EMT marker expression. Relative levels of the “epithelial” markers E-cadherin (CDH1) and p63, and the “mesenchymal’ markers ZEB1 and vimentin were measured by quantitative real-time RT-PCR.</p

FGFR1 selectively regulates invasion in “mesenchymal” bladder cancer cells.

<p>A. Left panel: effects of BGJ-398 on cell growth in two “mesenchymal’ (UM-UC3, UM-UC13) and two “epithelial” (UM-UC6, UM-UC9) cell lines that were found to be resistant to the anti-proliferative effects of the drug. Growth inhibition was measured at 48 h by MTT reduction. Mean ± SEM, n = 6. Center panel: concentration-dependent effects of BGJ-398 on invasion in the UM-UC3 and UM-UC13 cells. Invasion was measured using modified Boyden chambers and standard light microscopy as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057284#s2" target="_blank">Materials and Methods</a>. Mean ± SEM, n = 3. Right panel: effects of BGJ-398 on invasion in the UM-UC6 and UM-UC9 cells. Note that the drug had no effect on invasion in either cell line. B. Stable knockdown of FGFR1 or bFGF in cells transduced with lentiviral shRNAs. Relative mRNA levels were measured by quantititative real-time RT-PCR and protein levels were measured by immunoblotting. C. Effects of FGFR1 or bFGF knockdown on invasion. Left panels: percentages of cells that invaded through Matrigel in modified Boyden chambers were quantified by propidium iodide staining and confocal microscopy. The right panels display representative confocal images where the nuclei of the cells that invaded are pseudo-colored blue and the cells that did not invade are depicted in red.</p

FGFR3 levels predict sensitivity to BGJ-398-induced cell cycle arrest.

<p>A. Effects of BGJ-398 on cell proliferation in the drug-sensitive cells. In the left panel, cells were incubated for 48 h in the presence of the indicated concentrations of BGJ-398 and cell growth was measured by MTT reduction. Mean ± SEM, n = 6. In the center and right panels, UM-UC14 or RT4 cells were incubated with the indicated concentrations of BGJ-398 and the percentages of cells within each cell cycle quadrant were quantified by propidium iodide staining and FACS analysis. Mean ± SEM, n = 3. B. Sensitivity to the anti-proliferative effects of BGJ-398 correlates with FGFR3 expression but not with the presence of activating FGFR3 mutations. The level of growth inhibition observed after 48 h exposure to 1 µM BGJ-398 (as measured in MTT assays) was correlated with the relative level of FGFR3 (left panel) or FGFR1 (right panel) mRNA expression in a panel of 17 human BC cell lines.. C. Effects of FGFR3 knockdown on cell proliferation. Left panel: UM-UC14 or RT4 cells were transiently transfected with either non-targeting (NT) or FGFR3-specific siRNAs and cell growth was measured at 48 h by MTT reduction. Mean ± SEM, n = 6. Center and right panels: UM-UC14 or RT4 cells were transiently transfected with either non-targeting (NT) or FGFR3-specific siRNAs and percentages of cells within each phase of the cell cycle were quantified by propidium iodide staining and FACS analysis. Mean ± SEM, n = 3. Lower panel: the efficiency of FGFR3 silencing was measured by quantitative RT-PCR and immunoblotting.</p