Alex H. Beesley

Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR -- how well do they correlate?

BackgroundThe use of microarray technology to assess gene expression levels is now widespread in biology. The validation of microarray results using independent mRNA quantitation techniques remains a desirable element of any microarray experiment. To facilitate the comparison of microarray expression data between laboratories it is essential that validation methodologies be critically examined. We have assessed the correlation between expression scores obtained for 48 human genes using oligonucleotide microarrays and the expression levels for the same genes measured by quantitative real-time RT-PCR (qRT-PCR).ResultsCorrelations with qRT-PCR data were obtained using microarray data that were processed using robust multi-array analysis (RMA) and the MAS 5.0 algorithm. Our results indicate that when identical transcripts are targeted by the two methods, correlations between qRT-PCR and microarray data are generally strong (r = 0.89). However, we observed poor correlations between qRT-PCR and RMA or MAS 5.0 normalized microarray data for 13% or 16% of genes, respectively.ConclusionThese results highlight the complementarity of oligonucleotide microarray and qRT-PCR technologies for validation of gene expression measurements, while emphasizing the continuing requirement for caution in interpreting gene expression data.

The gene expression signature of relapse in paediatric acute lymphoblastic leukaemia: implications for mechanisms of therapy failure

Despite significant improvements in the treatment of childhood acute lymphoblastic leukaemia (ALL), the prognosis for relapsing patients remains poor. The aim of this study was to generate a transcriptional profile of relapsed ALL to increase our understanding of the mechanisms involved in therapy failure. RNA was extracted from 11 pairs of cryopreserved pre‐B ALL bone marrow specimens taken from the same patients at diagnosis and relapse, and analysed using HG‐U133A microarrays. Relapse specimens overexpressed genes that are involved with cell growth and proliferation, in keeping with their aggressive phenotype. When tested in 72 independent specimens of pre‐B ALL and T‐ALL, the identified genes could successfully differentiate between diagnosis and relapse in either lineage, indicating the existence of relapse mechanisms common to both. These genes have functions relevant for oncogenesis, drug resistance and metastasis, but are not related to classical multidrug‐resistance pathways. Increased expression of the top‐ranked gene (BSG) at diagnosis was significantly associated with adverse outcome. Several chromosomal loci, including 19p13, were identified as potential hotspots for aberrant gene expression in relapsed ALL. Our results provide evidence for a link between drug resistance and the microenvironment that has previously only been considered in the context of solid tumour biology.

Glucocorticoid resistance in T-lineage acute lymphoblastic leukaemia is associated with a proliferative metabolism

Glucocorticoids (GCs) are among the most important drugs for acute lymphoblastic leukaemia (ALL), yet despite their clinical importance, the exact mechanisms involved in GC cytotoxicity and the development of resistance remain uncertain. We examined the baseline profile of a panel of T-ALL cell lines to determine factors that contribute to GC resistance without prior drug selection. Transcriptional profiling indicated GC resistance in T-ALL is associated with a proliferative phenotype involving upregulation of glycolysis, oxidative phosphorylation, cholesterol biosynthesis and glutamate metabolism, increased growth rates and activation of PI3K/AKT/mTOR and MYC signalling pathways. Importantly, the presence of these transcriptional signatures in primary ALL specimens significantly predicted patient outcome. We conclude that in lymphocytes the activation of bioenergetic pathways required for proliferation may suppress the apoptotic potential and offset the metabolic crisis initiated by GC signalling. It is likely that the link between GC resistance and proliferation in T-ALL has not been fully appreciated to date because such effects would be masked in the context of current multiagent therapies. The data also provide the first evidence that altered expression of wild-type MLL may contribute to GC-resistant phenotypes. Our findings warrant the continued development of selective metabolic inhibitors for the treatment of ALL.

FusionFinder: a software tool to identify expressed gene fusion candidates from RNA-Seq data.

The hallmarks of many haematological malignancies and solid tumours are chromosomal translocations, which may lead to gene fusions. Recently, next-generation sequencing techniques at the transcriptome level (RNA-Seq) have been used to verify known and discover novel transcribed gene fusions. We present FusionFinder, a Perl-based software designed to automate the discovery of candidate gene fusion partners from single-end (SE) or paired-end (PE) RNA-Seq read data. FusionFinder was applied to data from a previously published analysis of the K562 chronic myeloid leukaemia (CML) cell line. Using FusionFinder we successfully replicated the findings of this study and detected additional previously unreported fusion genes in their dataset, which were confirmed experimentally. These included two isoforms of a fusion involving the genes BRK1 and VHL, whose co-deletion has previously been associated with the prevalence and severity of renal-cell carcinoma. FusionFinder is made freely available for non-commercial use and can be downloaded from the project website (http://bioinformatics.childhealthresearch.org.au/software/fusionfinder/).

Translating microarray data for diagnostic testing in childhood leukaemia

BackgroundRecent findings from microarray studies have raised the prospect of a standardized diagnostic gene expression platform to enhance accurate diagnosis and risk stratification in paediatric acute lymphoblastic leukaemia (ALL). However, the robustness as well as the format for such a diagnostic test remains to be determined. As a step towards clinical application of these findings, we have systematically analyzed a published ALL microarray data set using Robust Multi-array Analysis (RMA) and Random Forest (RF).MethodsWe examined published microarray data from 104 ALL patients specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent patient cohort.ResultsWe achieved very high overall ALL subgroup prediction accuracies of about 98%, and were able to verify the robustness of these genes in an independent panel of 68 specimens obtained from a different institution and processed in a different laboratory. Our study established that the selection of discriminating genes is strongly dependent on the analysis method. This may have profound implications for clinical use, particularly when the classifier is reduced to a small set of genes. We have demonstrated that as few as 26 genes yield accurate class prediction and importantly, almost 70% of these genes have not been previously identified as essential for class distinction of the six ALL subgroups.ConclusionOur finding supports the feasibility of qRT-PCR technology for standardized diagnostic testing in paediatric ALL and should, in conjunction with conventional cytogenetics lead to a more accurate classification of the disease. In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort and with microarray experiments being performed by a different research team.

Mechanism of relapse in pediatric acute lymphoblastic leukemia

Relapse following initial chemotherapy remains a barrier to survival in approximately 20% of children suffering from acute lymphoblastic leukemia (ALL). Recently, to investigate the mechanism of relapse, we analysed clonal populations in 27 pairs of matched diagnosis and relapse ALL samples using PCR-based detection of multiple antigen receptor gene rearrangements. These clonal markers revealed the emergence of apparently new populations at relapse in 13 patients. In those cases where the new ‘relapse clone’ could be detected in the diagnosis population, there was a close correlation between length of first remission and quantity of the relapse clone in the diagnosis sample. A shorter length of time to first relapse correlated with a higher quantity of the relapsing clone at diagnosis. This observation, together with demonstrated differential chemosensitivity between sub-clones at diagnosis, indicates that relapse in ALL patients may commonly involve selection of a minor intrinsically resistant sub-clone that is undetectable by routine PCR-based methods. From a clinical perspective, relapse prediction may be improved with strategies to detect minor potentially resistant sub-clones early during treatment, hence allowing intensification of therapy. Together with the availability of relevant in vivo experimental models and powerful technology for detailed analysis of patient specimens, this new information will help shape future experimentation towards targeted therapy for high-risk ALL.

High expression of connective tissue growth factor in pre-B acute lymphoblastic leukaemia

In recent years microarrays have been used extensively to characterize gene expression in acute lymphoblastic leukaemia (ALL). Few studies, however, have analysed normal haematopoietic cell populations to identify altered gene expression in ALL. We used oligonucleotide microarrays to compare the gene expression profile of paediatric precursor‐B (pre‐B) ALL specimens with two control cell populations, normal CD34+ and CD19+IgM− cells, to focus on genes linked to leukemogenesis. A set of eight genes was identified with a ninefold higher average expression in ALL specimens compared with control cells. All of these genes were significantly deregulated in an independent cohort of 101 ALL specimens. One gene, connective tissue growth factor (CTGF, also known as CCN2), had exceptionally high expression, which was confirmed in three independent leukaemia studies. Further analysis of CTGF expression in ALL revealed exclusive expression in B‐lineage, not T‐lineage, ALL. Within B‐lineage ALL approximately 75% of specimens were consistently positive for CTGF expression, however, specimens containing the E2A‐PBX1 translocation showed low or no expression. Protein studies using Western blot analysis demonstrated the presence of CTGF in ALL cell‐conditioned media. These findings indicate that CTGF is secreted by pre‐B ALL cells and may play a role in the pathophysiology of this disease.

In vitro cytotoxicity of nelarabine, clofarabine and flavopiridol in paediatric acute lymphoblastic leukaemia

The in vitro efficacies of three new drugs – clofarabine (CLOF), nelarabine (NEL) and flavopiridol (FP) – were assessed in a panel of acute lymphoblastic leukaemia (ALL) cell lines. The 50% inhibitory concentration (IC50) for CLOF across all lines was 188‐fold lower than that of NEL. B‐lineage, but not T‐lineage lines, were >7‐fold more sensitive to CLOF than cytosine arabinoside (ARAC). NEL IC50 was 25‐fold and 113‐fold higher than ARAC in T‐ and B‐lineage, respectively. T‐ALL cells were eightfold more sensitive to NEL than B‐lineage but there was considerable overlap. FP was more potent in vitro than glucocorticoids and thiopurines and at doses that recent phase I experience predicts will translate into clinical efficacy. Potential cross‐resistance of CLOF, NEL and FP was observed with many front‐line ALL therapeutics but not methotrexate or thiopurines. Methotrexate sensitivity was inversely related to that of NEL and FP. Whilst NEL was particularly effective in T‐ALL, a subset of patients with B‐lineage ALL might also be sensitive. CLOF appeared to be marginally more effective in B‐lineage than T‐ALL and has a distinct resistance profile that may prove useful in combination with other compounds. FP should be widely effective in ALL if sufficient plasma levels can be achieved clinically.

Novel BRD4-NUT fusion isoforms increase the pathogenic complexity in NUT midline carcinoma.

Nuclear protein in testis (NUT)-midline carcinoma (NMC) is a rare, aggressive disease typically presenting with a single t(15;19) translocation that results in the generation of a bromodomain-containing protein 4 (BRD4)–NUT fusion. PER-624 is a cell line generated from an NMC patient with an unusually complex karyotype that gave no initial indication of the involvement of the NUT locus. Analysis of PER-624 next-generation transcriptome sequencing (RNA-Seq) using the algorithm FusionFinder identified a novel transcript in which Exon 15 of BRD4 was fused to Exon 2 of NUT, therefore differing from all published NMC fusion transcripts. The three additional exons contained in the PER-624 fusion encode a series of polyproline repeats, with one predicted to form a helix. In the NMC cell line PER-403, we identified the ‘standard’ NMC fusion and two novel isoforms. Knockdown by small interfering RNA in either cell line resulted in decreased proliferation, increased cell size and expression of cytokeratins consistent with epithelial differentiation. These data demonstrate that the novel BRD4–NUT fusion in PER-624 encodes a functional protein that is central to the oncogenic mechanism in these cells. Genomic PCR indicated that in both PER-624 and PER-403, the translocation fuses an intron of BRD4 to a region upstream of the NUT coding sequence. Thus, the generation of BRD4–NUT fusion transcripts through post-translocation RNA-splicing appears to be a common feature of these carcinomas that has not previously been appreciated, with the mechanism facilitating the expression of alternative isoforms of the fusion. Finally, ectopic expression of wild-type NUT, a protein normally restricted to the testis, could be demonstrated in PER-403, indicating additional pathways for aberrant cell signaling in NMC. This study contributes to our understanding of the genetic diversity of NMC, an important step towards finding therapeutic targets for a disease that is refractory to current treatments.

Prediction of relapse in paediatric pre-B acute lymphoblastic leukaemia using a three-gene risk index

Despite high cure rates 25% of children with acute lymphoblastic leukaemia (ALL) relapse and have dismal outcome. Crucially, many are currently stratified as standard risk (SR) and additional markers to improve patient stratification are required. Here we have used diagnostic bone marrow specimens from 101 children with pre‐B ALL to examine the use of gene expression profiles (GEP) as predictors of long‐term clinical outcome. Patients were divided into two cohorts for model development and validation based on availability of specimen material. Initially, GEP from 55 patients with sufficient material were analysed using HG‐U133A microarrays, identifying an 18‐gene classifier (GC) that was more predictive of outcome than conventional prognostic parameters. After feature selection and validation of expression levels by quantitative reverse transcription polymerase chain reaction (qRT‐PCR), a three‐gene qRT‐PCR risk index [glutamine synthetase (GLUL), ornithine decarboxylase antizyme inhibitor (AZIN), immunoglobulin J chain (IGJ)] was developed that predicted outcome with an accuracy of 89% in the array cohort and 87% in the independent validation cohort. The data demonstrate the feasibity of using GEP to improve risk stratification in childhood ALL. This is particularly important for the identification of patients destined to relapse despite their current stratification as SR, as more intensive front‐line treatment options for these individuals are already available.