BioGPS Featured Article – Identification of Novel Tumor-Associated Cell Surface Sialoglycoproteins in Human Glioblastoma Tumors Using Quantitative Proteomics

BioGPS has become the valuable resource that it is because of the contributions from our wonderful user community. Thank you for contributing plugins, suggestions, and ideas–all of which have improved BioGPS for everyone. In order to celebrate the contributions of BioGPS users to the scientific research community, this series will feature publications and articles generated by BioGPS users. We sincerely hope you will join us in celebrating the fascinating work that YOU do.

This week, we will feature an article by an international team of researchers from France and the USA: Identification of Novel Tumor-Associated Cell Surface Sialoglycoproteins in Human Glioblastoma Tumors Using Quantitative Proteomics by François Autelitano, Denis Loyaux, Sébastien Roudières, Catherine Déon, Frédérique Guette, Philippe Fabre, Qinggong Ping, Su Wang, Romane Auvergne, Vasudeo Badarinarayana, Michael Smith, Jean-Claude Guillemot, Steven A. Goldman, Sridaran Natesan, Pascual Ferrara, and Paul August.

Dr. François Autelitano, the first author of this paper and one of the principal investigators, kindly answered our inquiries for this series.

  1. Who is the team behind the work that was published in Identification of Novel Tumor-Associated Cell Surface Sialoglycoproteins in Human Glioblastoma Tumors Using Quantitative Proteomics?.
    This work is the result of close collaboration between different groups:

  2.  

  3. What inspired the work published in Identification of Novel Tumor-Associated Cell Surface Sialoglycoproteins in Human Glioblastoma Tumors Using Quantitative Proteomics?
    The idea was to define an innovative strategy to discover potential new therapeutic targets for glioblastoma directly from patient tumor specimens.
  4.  

  5. Please provide a brief summary of the findings reported in your article, Identification of Novel Tumor-Associated Cell Surface Sialoglycoproteins in Human Glioblastoma Tumors Using Quantitative Proteomics.
    Glioblastoma multiform (GBM) remains an area of “unmet medical need” and innovative therapeutic strategies to eradicate residual tumor cells and prevent tumor recurrences are urgently needed. A major challenge of GBM research is the identification of novel molecular therapeutic targets and accurate diagnostic/prognostic biomarkers. Many clinical therapeutic targets of immunotoxins and ligand-directed toxins targeting high-grade glioma (HGG) cells are cell surface sialylated glycoproteins. In this study, we used the BioOrthogonal Chemical Reporter strategy (BOCR) in combination with label-free quantitative mass spectrometry (LFQ-MS) to characterize and accurately quantify the individual cell surface sialoproteome in human GBM tissues, in fetal and adult human astrocytes, and in human neural progenitor cells (NPCs). Our findings identified several known as well as new cell-surface antigens whose expression is predominantly restricted to human GBM tumors. Altogether, the results demonstrated the power of our quantitative sialoglyproteomics approach for the discovery of valuable new biomarkers and therapeutic targets for treatment of malignant gliomas.
  6.  

  7. How did the team learn about BioGPS?
    In my proteomics group, we have been using the BioGPS portals for many years now.
  8.  

  9. How did your team utilize BioGPS in this research?
    We examined protein expression patterns in normal human tissues, cancer and cell lines using high quality immunohistochemistry data available at the Human Protein Atlas web portal. We also examined the expression status of the corresponding transcripts in normal human tissues and cells using microarray datasets available at the BioGPS Gene Portal web site.
  10.  

  11. What are some future directions for the team behind this research?
    In the future, we will continue to use this approach to identify potential therapeutic targets for different types of cancer. The proteomic data obtained in our analyses will be compared with transcriptome data available at the BioGPS Gene Portal web site.
  12.  

Thanks again to Dr. François Autelitano for taking the time to answer our questions and for being a long time supporter of BioGPS. Click here to read their fascinating article. Have a look because these awesome researchers have made their compelling research open access–so you can read the whole exciting article for free!

Used BioGPS and cited it in your publication? Let us know! We would love to feature YOUR work, no matter how long ago it was published. BioGPS Featured Article Series only started recently, but we know your contributions to science is ongoing.


Leave a Reply

Your email address will not be published. Required fields are marked *