Use this URL to cite or link to this record in EThOS:
Title: Gene expression in oligodendrogliomas and oligoastrocytomas
Author: Shaw, Elisabeth Jane
ISNI:       0000 0004 2670 6714
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2008
Availability of Full Text:
Access from EThOS:
Access from Institution:
Oligodendrogliomas and oligoastrocytomas - histological subtypes of brain tumours respond to chemotherapy and frequently have combined loss of chromosome arms 1p and 19q. Oligodendroglial tumours with Ip/19q loss are more likely to respond to therapy, have longer progression-free survival and have better overall survival compared with tumours that do not have Ip/19q loss. Not all tumours with loss of Ip and 19q, however, are chemosensitive and some without loss also show clinical benefit. The molecular mechanisms giving rise to chemosensitivity are not well understood. This study was undertaken to identify genes. associated with molecular subtypes and response to therapy in a series of oligodendroglial tumours treated with pcV chemotherapy. Ultimately these genes might serve as genetic markers of therapeutic response or give insight into· the molecular basis of response to chemotherapy and the improved prognosis of tumours with Ip/19q loss. Gene identification was performed using DNA microarrays. The oligodendroglial tumours available for study were predominantly sampled pre-therapy by serial stereotactic biopsy. These small tissue samples yielded 49 to 1440ng of good quality total RNA and amplification was required to generate sufficient RNA for microarray hybridisations. A feasibility study demonstrated that RNA amplification of SOng of total RNA from biopsy tissues, combined with cDNA microarrays, could be used to examine gene expression in small stereotactic biopsy samples. The RiboAmpTM T7 linear amplification method used generated short amplified RNA fragments, with demonstrable loss of the 5' end of the mRNA transcript (Le. 3' bias). Therefore, a modified SMARTTM / T7 linear amplification method, developed at University Hospital Aintree, that provided sufficient yields of amplified RNA, with less 3' bias and longer fragment lengths, was used for further RNA amplifications. Gene expression profiling of a clinical series of 32 oligodendroglial tumours (9 OIl, 7 OAIl, 6 DIll, 10 OAIlI) treated by chemotherapy was performed using the modified SMARTTM / T7 linear amplification method and HGMP oligonucleotide arrays. Unsupervised hierarchical clustering identified subgroups associated with tumour grade and 1p/19q status. A greater heterogeneity in gene expression was seen between tumours than in multiple samples from the same tumours; in 78% of cases with multiple samples, these clustered together. Statistical analysis identified 94 genes> 2-fold differentially expressed with respect to Ip/19q status. Response to therapy was associated with Ip/19q status (Chi-squared ·p 2-fold differentially expressed between responders and non-responders. Twenty two of these were not located on Ip or 19q. Thirteen genes were selected for real-time PCR validation and array data confirmed for 11, with a trend evident in a twelfth. Novel genes associated with response to therapy in glioma included the neurotrophic factor receptor GFRA1, the peptidase FAP and the activator of Gprotein signalling RASD1. IQGAP1, INA, TGIF, NR2F2 and MYCBP were identified as being differentially expressed in oligodendroglial tumours with loss of Ip/19q. This study demonstrates that using microarrays for gene expression profiling of gliomas sampled by serial stereotactic biopsy is feasible. Expression profiling of a series of oligodendroglial tumours treated by chemotherapy identified differences in gene expression associated with molecular genetics and therapeutic response. Further investigation of identified genes, including GFRA1, FAP and IQGAP1, will determine if these genes have a role in response to therapy or improved prognosis.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral