Protein Tyrosine Kinase 6 Promotes Oncogenic Signaling at Cell Plasma Membrane in Prostate Cancer

Protein tyrosine kinase 6 (PTK6) is an intracellular Src-related tyrosine kinase that is localized to different cellular compartments due to the lack of an N-terminal myristoylation consensus sequence. In normal tissue, PTK6 is expressed in differentiated epithelial cells, and involved in promoting differentiation and mediating apoptosis in response to apoptotic stimuli. Elevated expression of PTK6 is detected in different types of human cancer including breast, colon, head and neck, melanoma and ovarian cancer, where it promotes cancer cell proliferation, migration and survival through different signaling pathways. In prostate cancer, we discovered elevated expression, aberrant localization and activation of PTK6. High levels of PTK6 predict low survival and high recurrence for human prostate cancer patients. As human prostate cancer progresses to advanced stages, PTK6 is translocated from nucleus to cytoplasm. This is also observed in a murine prostate cancer model. Activation of PTK6 is detected in both human and mouse prostate tumor samples. Interestingly, the pool of active PTK6, which is phosphorylated at tyrosine residue 342, is primarily associated with the cell plasma membrane. To investigate the role of PTK6 in prostate cancer, I identified several novel PTK6 substrates. I showed that PTK6 directly phosphorylates AKT, focal adhesion kinase (FAK) and p130 Crk-associated substrate (p130CAS) independent of Src family kinases. PTK6 positively regulates AKT activity by phosphorylating AKT at tyrosine residues 315 and 326. PTK6 also plays a critical role in promoting cell survival against anoikis by phosphorylating FAK and activating AKT survival signaling. In addition, PTK6 phosphorylates p130CAS and activates Erk5 to promote peripheral adhesion complex formation and cell migration. PTK6 is also involved in promoting epithelial-mesenchymal transition (EMT) of prostate cancer cells. In sum, I demonstrated that PTK6 promotes proliferation, migration, anoikis resistance, EMT, and invasion of prostate cancer cells through activating its substrates AKT, FAK and p130CAS. This study suggested that elevated PTK6 expression, translocation of PTK6 from nucleus to cytoplasm, and activation of PTK6 at plasma membrane in human prostate cancer might all contribute to the access and phosphorylation of these substrates and activation of their signaling pathways, therefore promoting prostate cancer progression

Normal To Tumor-like Cell Transition

My research focuses on the role of protein tyrosine kinase 6 (PTK6) in different aspects of cancer. Here is an image taken under fluorescence microscope, with DAPI staining (Blue) showing the nuclei of each BPH1 cell. BPH1 is a human benign prostatic hyperplasia cell line which is close to human normal prostate epithelia cell. A marker of epithelial cells, E-cadherin (Red) was detected in the cell membrane between cell-cell contacts. When membrane targeted PTK6 was expressed in BPH1 cells, it induced the formation of peripheral adhesion complexes (Green, visualized by phospho-tyrosine staining) around cell membrane. Interestingly, these “green” cells showed a remarkable loss of E-cadherin (Red). This phenomenon is called epithelial-mesenchymal transition (EMT) in biological terms, which is an important factor in human tumor progression. In other words, red cells represents normal cells and green cells represents tumor-like cells; membrane targeted PTK6 induces normal prostate cells to become tumor-like cells

Total Synthesis of (−)-Geissoschizol through Ir-Catalyzed Allylic Amidation as the Key Step

The iridium-catalyzed, Zn­(OTf)₂ promoted asymmetric allylic amidation of a secondary alcohol derived from tryptamine has been utilized to forge a tetrahydro-β-carboline. Based on this key step, a novel, facile, and enantioselective total synthesis of (−)-geissoschizol was achieved in 10 steps

Catalytic Enantioselective Synthesis of Key Propargylic Alcohol Intermediates of the Anti-HIV Drug Efavirenz

The catalytic, enantioselective synthesis of key propargylic alcohol intermediates toward the synthesis of the anti-HIV drug efavirenz is reported. Using a recently reported chiral-at-ruthenium catalyst (J. Am. Chem. Soc. 2017, 139, 4322), catalytic enantioselective alkynylations of 1-(2,5-dichloro­phenyl)-2,2,2-trifluoro­ethanone (99% yield, 95% ee) and 1-(5-chloro-2-nitrophenyl)-2,2,2-trifluoro­ethanone (97% yield, 99% ee) are achieved using catalyst loadings of merely 0.2 mol % (ca. 500 TON)

2D Representation of the Distance Matrix Computed from the Variable and Conserved Domains in a Group of Similar HKs

<p>The upper triangle shows the variable domains, the lower one the conserved domains. Amino acid sequence distances are calculated by the PROTDIST program using the Dayhoff PAM matrix. The sequence from each species is the best match (<i>E</i>-value < 1<i>E</i>-10) in that genome to the query E. coli gene. Abbreviations for organisms: Ec, Escherichia coli K12; Ps, Pseudomonas syringae pv. syringae B728a; Rm, Ralstonia metallidurans; Rs, Ralstonia solanacearum; Li, Listeria innocua; Tm, Thermotoga maritime; Ml, Mycobacterium leprae; Mt, Mycobacterium tuberculosis CDC1551; No, <i>Nostoc</i> sp. PCC 7120; Ef, Enterococcus faecalis; Bs, Bacillus subtilis; Ne, Nitrosomonas europaea; Sy, <i>Synechococcus</i> sp. PCC 7942; At, Agrobacterium tumefaciens. The PROTDIST program is included in the PHYLIP software package version 3.5 (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0020081#pbio-0020081-Felsenstein1" target="_blank">Felsenstein 1989</a>).</p

Paralogous Genes in SVGs

<div><p>(A) Paralog families in SVGs for four microorganisms. The x-axis shows the number of paralogs for each SVG. The y-axis shows the number of SVGs. The inset figure shows the percentage of genes with different numbers of paralogs for SVGs and fully conserved genes in E. coli genome. The x-axis is the number of paralogs, and the y-axis is the percentage.</p> <p>(B) Contingency tables to examine the dependence between SVG and paralogous gene. χ² statistics are computed using standard formula.</p></div

Variability Profile for Typical SVGs

<div><p>Blocks in the lines are conserved subsequences identified using the Pfam, BLOCKS, and PRINTS databases. In the variability profile, the x-axis is the amino acid position and the y-axis is the variability index (see Materials and Methods). Variable domains are marked by the black lines over the graph.</p> <p>(A) Cytosine-specific DNA methyltransferase of 355 amino acid long in H. pylori. Notice the variable domain in the middle and the variable segment in its N-terminal region, which is shorter than 70 amino acids and has no known function.</p> <p>(B) Virulence-associated protein homolog (VacB) of 644 amino acid long in H. pylori. It has two variable domains at the N- and C-termini.</p></div

Functional Classification of SVGs in Three Microorganisms

<div><p><i>M</i> is the total number of genes in a COG broad functional category, and <i>m</i> is the number of SVGs within that category. <i>r</i> ( = <i>m/M</i>) is the proportion of SVGs in that category. The <i>p</i>-value is calculated using a hypergeometric distribution: let <i>N</i> = number of genes in the genome; <i>n</i> = number of SVGs identified; <i>M</i> = number of genes belonging to a particular category; <i>m</i> = number of SVGs belonging to a particular category:</p> <p> </p><p></p><p></p> <p>The set of lineage-specific genes has been excluded in each genome to avoid the possible skew it brings to the estimation of significance. The significance level is set at 0.01. Cells with <i>p</i>-value less than 0.01 are shaded.</p></div

Abundance of SVGs in Different Functional Categories in Five Microorganisms

<p>The approximate total gene number for each organism is as follows: H. pylori, 1,566 genes; S. pneumoniae, 2,094 genes; N. meningitidis, 2,065 genes; E. coli, 4,289 genes; B. subtilis, 4,100 genes.</p

Classification of Three Groups of Genes from a Single Genome, H. pylori, in 2D Space

<p>The x-axis is the length of the variable region and the y-axis is the number of possible homologs a gene has from a BLAST search. The variable region length for a lineage-specific gene is defined as the length of the gene so that they naturally cluster onto the x-axis. Multiple variable regions in one gene are represented separately.</p