Histone deacetylase inhibitor valproic acid suppresses the growth and increases the androgen responsiveness of prostate cancer cells.

We identified the molecular target by histone deacetylase (HDAC) inhibitors for exploring their potential prostate cancer (PCa) therapy. Upon HDAC inhibitors-treatment, LNCaP cell growth was suppressed, correlating with increased cellular prostatic acid phosphatase (cPAcP) expression, an authentic protein tyrosine phosphatase. In those cells, ErbB-2 was dephosphorylated, histone H3/H4 acetylation and methylation increased and cyclin proteins decreased. In PAcP shRNA-transfected C-81 cells, valproic acid (VPA) efficacy of growth suppression was diminished. Further, VPA pre-treatment enhanced androgen responsiveness of C-81, C4-2 and MDA PCa2b-AI cells. Thus, cPAcP expression is involved in growth suppression by HDAC inhibitors in PCa cells, and VPA pre-treatments increase androgen responsiveness

LINKIN, a new transmembrane protein necessary for cell adhesion

In epithelial collective migration, leader and follower cells migrate while maintaining cell-cell adhesion and tissue polarity. We have identified a conserved protein and interactors required for maintaining cell adhesion during a simple collective migration in the developing C. elegans male gonad. LINKIN is a previously uncharacterized, transmembrane protein conserved throughout Metazoa. We identified seven atypical FG-GAP domains in the extracellular domain, which potentially folds into a β-propeller structure resembling the α-integrin ligand-binding domain. C. elegans LNKN-1 localizes to the plasma membrane of all gonadal cells, with apical and lateral bias. We identified the LINKIN interactors RUVBL1, RUVBL2, and α-tubulin by using SILAC mass spectrometry on human HEK 293T cells and testing candidates for lnkn-1-like function in C. elegans male gonad. We propose that LINKIN promotes adhesion between neighboring cells through its extracellular domain and regulates microtubule dynamics through RUVBL proteins at its intracellular domain

Malignant phyllodes tumors display mesenchymal stem cell features and aldehyde dehydrogenase/disialoganglioside identify their tumor stem cells.

IntroductionAlthough breast phyllodes tumors are rare, there is no effective therapy other than surgery. Little is known about their tumor biology. A malignant phyllodes tumor contains heterologous stromal elements, and can transform into rhabdomyosarcoma, liposarcoma and osteosarcoma. These versatile properties prompted us to explore their possible relationship to mesenchymal stem cells (MSCs) and to search for the presence of cancer stem cells (CSCs) in phyllodes tumors.MethodsParaffin sections of malignant phyllodes tumors were examined for various markers by immunohistochemical staining. Xenografts of human primary phyllodes tumors were established by injecting freshly isolated tumor cells into the mammary fat pad of non-obese diabetic-severe combined immunodeficient (NOD-SCID) mice. To search for CSCs, xenografted tumor cells were sorted into various subpopulations by flow cytometry and examined for their in vitro mammosphere forming capacity, in vivo tumorigenicity in NOD-SCID mice and their ability to undergo differentiation.ResultsImmunohistochemical analysis revealed the expression of the following 10 markers: CD44, CD29, CD106, CD166, CD105, CD90, disialoganglioside (GD2), CD117, Aldehyde dehydrogenase 1 (ALDH), and Oct-4, and 7 clinically relevant markers (CD10, CD34, p53, p63, Ki-67, Bcl-2, vimentin, and Globo H) in all 51 malignant phyllodes tumors examined, albeit to different extents. Four xenografts were successfully established from human primary phyllodes tumors. In vitro, ALDH+ cells sorted from xenografts displayed approximately 10-fold greater mammosphere-forming capacity than ALDH- cells. GD2+ cells showed a 3.9-fold greater capacity than GD2- cells. ALDH+/GD2+cells displayed 12.8-fold greater mammosphere forming ability than ALDH-/GD2- cells. In vivo, the tumor-initiating frequency of ALDH+/GD2+ cells were up to 33-fold higher than that of ALDH+ cells, with as few as 50 ALDH+/GD2+ cells being sufficient for engraftment. Moreover, we provided the first evidence for the induction of ALDH+/GD2+ cells to differentiate into neural cells of various lineages, along with the observation of neural differentiation in clinical specimens and xenografts of malignant phyllodes tumors. ALDH+ or ALDH+/GD2+ cells could also be induced to differentiate into adipocytes, osteocytes or chondrocytes.ConclusionsOur findings revealed that malignant phyllodes tumors possessed many characteristics of MSC, and their CSCs were enriched in ALDH+ and ALDH+/GD2+ subpopulations

Cellular prostatic acid phosphatase (cPAcP) serves as a useful biomarker of histone deacetylase (HDAC) inhibitors in prostate cancer cell growth suppression.

BACKGROUND: Prostate cancer (PCa) is the most commonly diagnosed solid tumor and the second leading cancer death in the United States, and also one of the major cancer-related deaths in Chinese. Androgen deprivation therapy (ADT) is the first line treatment for metastatic PCa. PCa ultimately relapses with subsequent ADT treatment failure and becomes castrate-resistant (CR). It is important to develop effective therapies with a surrogate marker towards CR PCa. METHOD: Histone deacetylase (HDAC) inhibitors were examined to determine their effects in androgen receptor (AR)/cellular prostatic acid phosphatase (cPAcP)-positive PCa cells, including LNCaP C-33, C-81, C4-2 and C4-2B and MDA PCa2b androgen-sensitive and androgen-independent cells, and AR/cPAcP-negative PCa cells, including PC-3 and DU 145 cells. Cell growth was determined by cell number counting. Western blot analyses were carried out to determine AR, cPAcP and PSA protein levels. RESULTS: cPAcP protein level was increased by HDAC inhibitor treatment. Valproic acid, a HDAC inhibitor, suppressed the growth of AR/cPAcP-positive PCa cells by over 50% in steroid-reduced conditions, higher than on AR/cPAcP-negative PCa cells. Further, HDAC inhibitor pretreatments increased androgen responsiveness as demonstrated by PSA protein level quantitation. CONCLUSION: Our results clearly demonstrate that HDAC inhibitors can induce cPAcP protein level, increase androgen responsiveness, and exhibit higher inhibitory activities on AR/cPAcP-positive PCa cells than on AR/cPAcP-negative PCa cells. Upon HDAC inhibitor pretreatment, PSA level was greatly elevated by androgens. This data indicates the potential clinical importance of cPAcP serving as a useful biomarker in the identification of PCa patient sub-population suitable for HDAC inhibitor treatment

Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann–Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. RESULTS: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence… CONCLUSIONS: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence

SinicView: A visualization environment for comparisons of multiple nucleotide sequence alignment tools

BACKGROUND: Deluged by the rate and complexity of completed genomic sequences, the need to align longer sequences becomes more urgent, and many more tools have thus been developed. In the initial stage of genomic sequence analysis, a biologist is usually faced with the questions of how to choose the best tool to align sequences of interest and how to analyze and visualize the alignment results, and then with the question of whether poorly aligned regions produced by the tool are indeed not homologous or are just results due to inappropriate alignment tools or scoring systems used. Although several systematic evaluations of multiple sequence alignment (MSA) programs have been proposed, they may not provide a standard-bearer for most biologists because those poorly aligned regions in these evaluations are never discussed. Thus, a tool that allows cross comparison of the alignment results obtained by different tools simultaneously could help a biologist evaluate their correctness and accuracy. RESULTS: In this paper, we present a versatile alignment visualization system, called SinicView, (for Sequence-aligning INnovative and Interactive Comparison VIEWer), which allows the user to efficiently compare and evaluate assorted nucleotide alignment results obtained by different tools. SinicView calculates similarity of the alignment outputs under a fixed window using the sum-of-pairs method and provides scoring profiles of each set of aligned sequences. The user can visually compare alignment results either in graphic scoring profiles or in plain text format of the aligned nucleotides along with the annotations information. We illustrate the capabilities of our visualization system by comparing alignment results obtained by MLAGAN, MAVID, and MULTIZ, respectively. CONCLUSION: With SinicView, users can use their own data sequences to compare various alignment tools or scoring systems and select the most suitable one to perform alignment in the initial stage of sequence analysis