Expression and Clinical Implication of Autophagy-Associated Protein p62 in Osteosarcoma.

PURPOSE: Recent studies highlight the role of autophagy in cancer tumorigenesis, recurrence, metastasis, and chemoresistance. p62 is an adapter protein that is crucial for the autophagy pathway. In this study, we will describe the expression of p62 and its correlation with clinic prognosis in osteosarcoma. METHODS: Western blot was used to test the expression of p62 in osteosarcoma cell lines (U2OS, KHOS, MG63, Saos-2, U2OSR2, KHOSR2, and 143B). A tissue microarray (TMA) was analyzed by immunohistochemistry to determine the expression levels of p62 in osteosarcoma patients and evaluate any correlation between p62 and clinical characteristics in osteosarcoma patients. RESULTS: p62 was expressed differently in all cell lines. The TMA also showed differential expression in osteosarcoma tissues. Seventy-five of 79 (94.9%) patient tissues exhibited p62 immunostaining, ranging from no staining (4 of 97, 5.1%) to 1+ staining (40 of 79, 50.6%), 2+ staining (17 of 79, 21.5%), and 3+ staining (18 of 79, 22.8%). The low staining (1+) was classified as the p62 weak group (50.6%), the medium staining (2+) and intense staining (3+) were classified as the p62 strong group (44.3%). Analyzing the clinical data of the osteosarcoma TMA, we found that the 5-year survival rate of patients with weak p62 expression was significantly lower than that of the patients with strong p62 expression (p = 0.0165). Furthermore, the decreased p62 expression may be associated with higher metastatic and chemoresistant rates in osteosarcoma patients. CONCLUSION: Our results suggest that p62 may be an effective predictor of prognosis and a potential target for therapy in osteosarcoma.

Advances in chromosomal translocations and fusion genes in sarcomas and potential therapeutic applications.

Chromosomal translocations and fusion genes are very common in human cancer especially in subtypes of sarcomas, such as rhabdomyosarcoma, Ewing's sarcoma, synovial sarcoma and liposarcoma. The discovery of novel chromosomal translocations and fusion genes in different tumors are due to the advancement of next-generation sequencing (NGS) technologies such as whole genome sequencing. Recently, many novel chromosomal translocations and gene fusions have been identified in different types of sarcoma through NGS approaches. In addition to previously known sarcoma fusion genes, these novel specific fusion genes and associated molecular events represent important targets for novel therapeutic approaches in the treatment of sarcomas. This review focuses on recent advances in chromosomal translocations and fusion genes in sarcomas and their potential therapeutic applications in the treatment of sarcomas.

Expression and Therapeutic Potential of SOX9 in Chordoma.

Purpose: Conventional chemotherapeutic agents are ineffective in the treatment of chordoma. We investigated the functional roles and therapeutic relevance of the sex-determining region Y (SRY)-box 9 (SOX9) in chordoma.Experimental Design: SOX9 expression was examined by immunohistochemistry (IHC) using 50 chordoma tissue samples. SOX9 expression in chordoma cell lines was examined by Western blot and immunofluorescent assays. We used synthetic human SOX9 siRNA to inhibit the expression of SOX9. Cell proliferation ability and cytotoxicity of inhibiting SOX9 were assessed by 3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT) and clonogenic assays. The effect of SOX9 knockdown on chordoma cell motility was evaluated by a wound-healing assay and a Transwell invasion chamber assay. Knockdown of SOX9 induced apoptosis, cell-cycle arrest, as well as decreased expression of cancer stem cell markers were determined by Western blot and flow cytometric assays. The effect of the combination of SOX9 siRNA and the chemotherapeutic drug doxorubicin/cisplatin on chordoma cells was assessed by an MTT assay.Results: Tissue microarray and IHC analysis showed that SOX9 is broadly expressed in chordomas and that higher expression levels of SOX9 correlated with a poor prognosis. RNA interference (RNAi)-mediated knockdown of SOX9 inhibited chordoma cell growth, decreased cell motility, and induced apoptosis as well as cell-cycle arrest. Moreover, the combination of SOX9 inhibition and chemotherapeutic drugs had an enhanced anti-cancer effect on chordoma cells.Conclusions: Our results demonstrate that SOX9 plays a crucial role in chordoma. Targeting SOX9 provides a new rationale for treatment of chordoma. Clin Cancer Res; 23(17); 5176-86. ©2017 AACR.

An imprinted non-coding genomic cluster at 14q32 defines clinically relevant molecular subtypes in osteosarcoma across multiple independent datasets.

BACKGROUND: A microRNA (miRNA) collection on the imprinted 14q32 MEG3 region has been associated with outcome in osteosarcoma. We assessed the clinical utility of this miRNA set and their association with methylation status. METHODS: We integrated coding and non-coding RNA data from three independent annotated clinical osteosarcoma cohorts (n = 65, n = 27, and n = 25) and miRNA and methylation data from one in vitro (19 cell lines) and one clinical (NCI Therapeutically Applicable Research to Generate Effective Treatments (TARGET) osteosarcoma dataset, n = 80) dataset. We used time-dependent receiver operating characteristic (tdROC) analysis to evaluate the clinical value of candidate miRNA profiles and machine learning approaches to compare the coding and non-coding transcriptional programs of high- and low-risk osteosarcoma tumors and high- versus low-aggressiveness cell lines. In the cell line and TARGET datasets, we also studied the methylation patterns of the MEG3 imprinting control region on 14q32 and their association with miRNA expression and tumor aggressiveness. RESULTS: In the tdROC analysis, miRNA sets on 14q32 showed strong discriminatory power for recurrence and survival in the three clinical datasets. High- or low-risk tumor classification was robust to using different microRNA sets or classification methods. Machine learning approaches showed that genome-wide miRNA profiles and miRNA regulatory networks were quite different between the two outcome groups and mRNA profiles categorized the samples in a manner concordant with the miRNAs, suggesting potential molecular subtypes. Further, miRNA expression patterns were reproducible in comparing high-aggressiveness versus low-aggressiveness cell lines. Methylation patterns in the MEG3 differentially methylated region (DMR) also distinguished high-aggressiveness from low-aggressiveness cell lines and were associated with expression of several 14q32 miRNAs in both the cell lines and the large TARGET clinical dataset. Within the limits of available CpG array coverage, we observed a potential methylation-sensitive regulation of the non-coding RNA cluster by CTCF, a known enhancer-blocking factor. CONCLUSIONS: Loss of imprinting/methylation changes in the 14q32 non-coding region defines reproducible previously unrecognized osteosarcoma subtypes with distinct transcriptional programs and biologic and clinical behavior. Future studies will define the precise relationship between 14q32 imprinting, non-coding RNA expression, genomic enhancer binding, and tumor aggressiveness, with possible therapeutic implications for both early- and advanced-stage patients.

Getting to the edge: protein dynamical networks as a new frontier in plant-microbe interactions.

A systems perspective on diverse phenotypes, mechanisms of infection, and responses to environmental stresses can lead to considerable advances in agriculture and medicine. A significant promise of systems biology within plants is the development of disease-resistant crop varieties, which would maximize yield output for food, clothing, building materials, and biofuel production. A systems or "-omics" perspective frames the next frontier in the search for enhanced knowledge of plant network biology. The functional understanding of network structure and dynamics is vital to expanding our knowledge of how the intercellular communication processes are executed. This review article will systematically discuss various levels of organization of systems biology beginning with the building blocks termed "-omes" and ending with complex transcriptional and protein-protein interaction networks. We will also highlight the prevailing computational modeling approaches of biological regulatory network dynamics. The latest developments in the "-omics" approach will be reviewed and discussed to underline and highlight novel technologies and research directions in plant network biology.