Biospecimen Research Services (BRS)

As cancer therapies become more targeted to specific types and sub-classes of cancer, the demand for quality biospecimens from patients and annotated data increases. Continued investigations into the best way to collect and store biospecimens, as well as manage, manipulate and share data, is crucial to the advancement of translational research. Our biospecimens research services ensures delivery of the highest quality biospecimens to paediatric cancer researchers by the Tumour Bank team and other biobanks around the world. Our approaches include the application of data analytics with the goal to integrate data analysis into the clinic, so that doctors can better diagnose and treat children with cancer.

Tumour Bank Collaborations

• Bespoke therapy for young cancer patients 
• Quantum computation and intelligent systems - UTS Collaboration

Request Biomaterial

• Please contact Dr Li Zhou; 02 9845 3028 or li.zhou@health.nsw.gov.au

The research team

> Associate Professor Daniel Catchpoole, Research Group Leader, email: daniel.catchpoole@health.nsw.gov.au

New technology and data mining strategies mean it is now possible to paint a clear picture of the genetic profiles of tumours. This means cancers can be more accurately classified and treatments tailored to patients’ unique needs.

Dan is head of the Tumour Bank and one of the founding members of the Australian Biospecimens Network. He established microarray technology within the Children's Cancer Research Unit and continues to advance e-medicine approaches in cancer research and treatment. His research focuses on improving data visualisation to advance cancer pers acute lymphoblastic leukaemia and neuroblastoma, as well as cancer prone syndromes in children, namely Beckwith Wiedemann syndrome. More information can be found on Dan's University of Sydney profile page

> Other research team members:

• Dr Li Zhou, Research Officer

• Natalie Gabrael, Clinical Research Associate

• Aysen Yuksel, Research Assistant

Key publications

Catchpoole D (2016) 'Biohoarding': treasures not seen, stories not told. J Health Services Res & Policy 21(2): 140-142

Anaissi A, Goyal M, Catchpoole D, Braytee A, Kennedy P (2015) Case-Based Retrieval Framework for Gene Expression Data. Cancer Informatics 14: 21-31

Chen L, Shern J, Wei J, Yohe M, Song Y, Hurd L, Hongling L, Catchpoole D, Skapek S, Barr F, et al (2015) Clonality and evolutionary history of rhabdomyosarcoma. PLoS Genetics 11(3): 1-25

Song R, Catchpoole D, Kennedy P, Li J (2015) Identification of lung cancer miRNA-miRNA co-regulation networks through a progressive data refining approach. Journal of Theoretical Biology 380: 271-279

Rush A, Battisti R, Barton B, Catchpoole D (2015) Opinions of Young Adults on Re-Consenting for Biobanking. The Journal of Pediatrics 167(4): 925-930

Zhou L, Catchpoole D (2015) Spanning the genomics era: the vital role of a single institution biorepository for childhood cancer research over a decade. Translational Pediatrics 4(2): 93-106

Zhou L, Nath N, Markovich O, Yuksel A, Roberts A, Catchpoole D (2015) The Tumour Bank of The Children's Hospital at Westmead. Biopreservation and Biobanking 13(2): 147-148

Brohl A, Solomon D, Chang W, Wang J, Song Y, Sindiri S, Patidar R, Hurd L,Chen L, Shern J, Gerard J, Kim JS, Lopez-Guerrero JA, Machado I, Wai D,  Picci P, Triche T, Horvai A, Miettinen M, Wei J, Catchpoole D, et al. (2014) The genomic landscape of the Ewing sarcoma family of tumors reveals recurrent STAG2 mutation. PLoS Genetics 10(7) e1004475: 1-13

Shern JF, Chen L, Chmielecki J, Wei JS, Patidar R, Rosenberg M, Ambrogio L, Auclair D, Wang J, Song YK, Tolman C, Hurd L, Liao H, Zhang S, Bogen D, Brohl A, Sindiri S, Catchpoole DR, et al. (2014) Comprehensive genomic analysis of rhabdomyosarcoma reveals a landscape of alterations affecting a common genetic axis in fusion-positive and fusion-negative tumours. Cancer Discovery 4(2): 216231

Tafavogh S, Catchpoole DR, Kennedy PJ (2014) Cellular quantitative analysis of neuroblastoma tumor and splitting overlapping cells. BMC Bioinformatics 15: 272