The pancreatic cancer database – an excellent resource

The pancreatic cancer database1 is a one-stop shop for finding information derived from the literature on the expression levels of mRNA, miRNA, and protein in pancreatic cancer:

http://pancreaticcancerdatabase.org/index.php

It has been produced by the team behind the 2009 PLOS Medicine paper2 which catalogued a list of potential biomarkers for pancreatic cancer using an algorithm that examined microarray databases and the published literature for overexpressed mRNAs and proteins.

You can search by gene or protein identifiers or browse by gene symbol. All results are hyperlinked to the relevant PubMed entries.

It should be noted that the database is not complete. For example searches for “CDCP1” (there is data in the literature) or “IL24” yield no results.

The database is a useful resource to quickly check the status of a gene of interest. However the results are not fine grained. Microarray data is reported as average fold change. Pancreatic cancer is an extremely heterogeneous disease and it is worth keeping in mind that average fold change can mask important outliers. It is the outliers that are interesting/ important.

It is certainly worth taking a closer look at the underlying microarray data. This will require some processing and analysis. However the R statistical programming language and various web resources such as CARMAweb3 make this relatively straightforward:

https://carmaweb.genome.tugraz.at/carma/

  1. Thomas, Joji Kurian, Min-Sik Kim, Lavanya Balakrishnan, Vishalakshi Nanjappa, Rajesh Raju, Arivusudar Marimuthu, Aneesha Radhakrishnan, et al. ‘Pancreatic Cancer Database: An Integrative Resource for Pancreatic Cancer’. Cancer Biology & Therapy 15, no. 8 (August 2014): 963–67. doi:10.4161/cbt.29188.
  2.  Harsha, H. C., Kumaran Kandasamy, Prathibha Ranganathan, Sandhya Rani, Subhashri Ramabadran, Sashikanth Gollapudi, Lavanya Balakrishnan, et al. ‘A Compendium of Potential Biomarkers of Pancreatic Cancer’. PLoS Medicine 6, no. 4 (7 April 2009): e1000046. doi:10.1371/journal.pmed.1000046.
  3.  Rainer, J., F. Sanchez-Cabo, G. Stocker, A. Sturn, and Z. Trajanoski. ‘CARMAweb: Comprehensive R- and Bioconductor-Based Web Service for Microarray Data Analysis’. Nucleic Acids Research 34, no. Web Server (1 July 2006): W498–503. doi:10.1093/nar/gkl038.
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