Overexpression of MYC oncogene is highly prevalent in many malignancies such as aggressive triple-negative breast cancers (TNBCs) and it is associated with very poor outcome. Despite decades of research, attempts to effectively inhibit MYC, particularly with small molecules, still remain challenging due to the featureless nature of its protein structure. Herein, we describe the engineering of the dominant-negative MYC peptide (OmoMYC) linked to a functional penetrating ‘Phylomer’ peptide (FPPa) as a therapeutic strategy to inhibit MYC in TNBC. We found FPPa-OmoMYC to be a potent inducer of apoptosis (with IC50 from 1–2 µM) in TNBC cells with negligible effects in non-tumorigenic cells. Transcriptome analysis of FPPa-OmoMYC-treated cells indicated that the fusion protein inhibited MYC-dependent networks, inducing dynamic changes in transcriptional, metabolic, and apoptotic processes. We demonstrated the efficacy of FPPa-OmoMYC in inhibiting breast cancer growth when injected orthotopically in TNBC allografts. Lastly, we identified strong pharmacological synergisms between FPPa-OmoMYC and chemotherapeutic agents. This study highlights a novel therapeutic approach to target highly aggressive and chemoresistant MYC-activated cancers.

Cell penetrating peptides (CPPs) offer great potential to deliver therapeutic molecules to previously inaccessible intracellular targets. However, many CPPs are inefficient and often leave their attached cargo stranded in the cell’s endosome. We report a versatile platform for the isolation of peptides delivering a wide range of cargos into the cytoplasm of cells. We used this screening platform to identify multiple “Phylomer” CPPs, derived from bacterial and viral genomes. These peptides are amenable to conventional sequence optimization and engineering approaches for cell targeting and half-life extension. We demonstrate potent, functional delivery of protein, peptide, and nucleic acid analog cargos into cells using Phylomer CPPs. We validate in vivo activity in the cytoplasm, through successful transport of an oligonucleotide therapeutic fused to a Phylomer CPP in a disease model for Duchenne’s muscular dystrophy. This report thus establishes a discovery platform for identifying novel, functional CPPs to expand the delivery landscape of druggable intracellular targets for biological therapeutics.

The ability of cell penetrating peptides (CPPs) to deliver biologically relevant cargos into cells is becoming more important as targets in the intracellular space continue to be explored. We have developed two assays based on CPP-dependent, intracellular delivery of TEM-1 β-lactamase enzyme, a functional biological molecule comparable in size to many protein therapeutics. The first assay focuses on the delivery of full-length β-lactamase to evaluate the internalization potential of a CPP sequence. The second assay uses a split-protein system where one component of β-lactamase is constitutively expressed in the cytoplasm of a stable cell line and the other component is delivered by a CPP. The delivery of a split β-lactamase component evaluates the cytosolic delivery capacity of a CPP. We demonstrate that these assays are rapid, flexible and have potential for use with any cell type and CPP sequence. Both assays are validated using canonical and novel CPPs, with limits of detection from <500 nM to 1 µM. Together, the β-lactamase assays provide compatible tools for functional characterization of CPP activity and the delivery of biological cargos into cells.

Efficient cargo uptake is essential for cell-penetrating peptide (CPP) therapeutics, which deliver widely diverse cargoes by exploiting natural cell processes to penetrate the cell's membranes. Yet most current CPP activity assays are hampered by limitations in assessing uptake, including confounding effects of conjugated fluorophores or ligands, indirect read-outs requiring secondary processing, and difficulty in discriminating internalization from endosomally trapped cargo. Split-complementation Endosomal Escape (SEE) provides the first direct assay visualizing true cytoplasmic-delivery of proteins at biologically relevant concentrations. The SEE assay has minimal background, is amenable to high-throughput processes, and adaptable to different transient and stable cell lines. This split-GFP-based platform can be useful to study transduction mechanisms, cellular imaging, and characterizing novel CPPs as pharmaceutical delivery agents in the treatment of disease.

Using cortical neuronal cultures and glutamic acid excitotoxicity and oxygen-glucose deprivation (OGD) stroke models, we. demonstrated that poly-arginine and arginine-rich cell-penetrating peptides (CPPs), are highly neuroprotective, with efficacy increasing with increasing arginine content, have the capacity to reduce glutamic acid-induced neuronal calcium influx and require heparan sulfate preotoglycan-mediated endocytosis to induce a neuroprotective effect. Furthermore, neuroprotection could be induced with immediate peptide treatment or treatment up to 2 to 4 hours before glutamic acid excitotoxicity or OGD, and with poly-arginine-9 (R9) when administered intravenously after stroke onset in a rat model. In contrast, the JNKI-1 peptide when fused to the (non-arginine) kFGF CPP, which does not rely on endocytosis for uptake, was not neuroprotective in the glutamic acid model; the kFGF peptide was also ineffective. Similarly, positively charged poly-lysine-10 (K10) and R9 fused to the negatively charged poly-glutamic acid-9 (E9) peptide (R9/E9) displayed minimal neuroprotection after excitotoxicity. These results indicate that peptide positive charge and arginine residues are critical for neuroprotection, and have led us to hypothesize that peptide-induced endocytic internalization of ion channels is a potential mechanism of action. The findings also question the mode of action of different neuroprotective peptides fused to arginine-rich CPPs.

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.

In the last four decades the survival of patients with newly diagnosed childhood T-cell acute lymphoblastic leukaemia (T-ALL) has improved dramatically. In sharp contrast, relapsed T-ALL continues to confer a dismal prognosis. We sought to determine if gene expression profiling could uncover a signature of outcome for children with T-ALL. Using 12 patient specimens obtained before therapy started, we examined the gene expression profile by oligonucleotide microarrays. We identified three genes, CFLAR, NOTCH2 and BTG3, whose expression at the time of diagnosis accurately distinguished the patients according to disease outcome. These genes are involved in the regulation of apoptosis and cellular proliferation. The prognostic value of the three predictive genes was assessed in an independent cohort of 25 paediatric T-ALL patients using quantitative real-time reverse transcription polymerase chain reaction. Patients assigned to the adverse outcome group had a significantly higher cumulative incidence of relapse compared with patients assigned to the favourable outcome group (46% vs. 8%, P = 0.029). Five-year overall survival was also significantly worse in the patients assigned to the adverse outcome group (P = 0.0039). The independent influence of the 3-gene predictor was confirmed by multivariate analysis. Our study provides proof of principle that genome-wide expression profiling can detect novel molecular prognostic markers in paediatric T-ALL.

BACKGROUND:Recent 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).METHODS:We 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.RESULTS:We 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.CONCLUSION:Our 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.

The cells of solid tumours are known to have an altered metabolism, with high rates of glucose uptake and glycolysis, which results in the excessive production of lactate. To date there has been no definitive research documenting metabolic changes in acute lymphoblastic leukaemia (ALL) cells. In order to investigate whether ALL cells have an altered metabolism, we initially compared the transcriptional profiles of 22 specimens from paediatric patients diagnosed with ALL to five CD34+ specimens isolated from bone marrow, which was verified in an independent cohort of 101 specimens. Profiling revealed the upregulation of genes facilitating glycolysis in the ALL specimens compared to the CD34+ specimens, while those involved in the tricarboxylic acid cycle were downregulated. Functional studies supported the microarray findings threefold: (1) higher expression of the glucose transport protein glucose transporter 1 in ALL compared to CD34+ specimens, (2) the excessive production of lactate in ALL cell lines and (3) sensitivity of ALL cell lines to the glycolysis inhibitor 2-deoxy-D-glucose. While metabolic alterations have been well documented in solid tumours, this is the first study to provide direct evidence for the existence of metabolic changes in the leukaemic cells of ALL patients. The finding offers new options for targeted therapy for ALL patients.

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.

BACKGROUND:The 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).RESULTS:Correlations 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.CONCLUSION:These 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.

Large-scale gene expression profiling using microarray technology is often limited by the amount of tissue or cells available. A number of RNA amplification protocols have been published to overcome this problem. However, additional amplification steps can result in both a 3′ bias and poor reproducibility for low abundance transcripts. We performed microarray experiments using HG-U133A GeneChip arrays to ascertain whether less than the recommended amount of RNA can be used, thus avoiding additional amplification steps. In a titration experiment, 2–10 µg of total RNA from a single cryopreserved patient specimen was used to prepare biotinylated cRNA, and the recommended standard amount of 15 µg of each preparation was used for hybridization. Statistical analysis using box plots, correlation coefficients, MvA plots, and concordance percentages revealed almost identical levels of gene expression, independent of the amount of RNA used for target preparation. Most importantly, there was no statistically significant difference when the concordance percentages for low abundance genes were compared, demonstrating that as little as 2 µg of total RNA is sufficient to perform GeneChip analysis.

HOX11 is a homeobox gene originally identified at a chromosomal breakpoint in T-cell acute lymphoblastic leukemia (T-ALL). It is one of the most frequently deregulated genes in T-ALL, although the precise role of HOX11 in leukemogenesis as well as in normal development remains obscure. To gain more insight into the functional role of HOX11, we utilized a microarray model system to characterize the gene expression network that it directs. Using one of our T-ALL cell lines that had been stably transfected to express HOX11 and high-density oligonucleotide HG-U95A arrays, we identified a large number of differentially expressed genes in response to the enforced expression of HOX11. We focused on examining genes found to be up-regulated according to the microarray analysis and selected three putative target genes, NFKB2, SMARCD3, and NR4A3, for further investigation. We could not only confirm the up-regulation of NR4A3 by an independent method in all clones expressing HOX11, but luciferase reporter assays demonstrated that the effect that HOX11 exerted on the proximal promoter of NR4A3 was dependent on the presence of an intact homeodomain, providing support for the idea that HOX11 manifests its regulatory function via its action as a transcription factor.

HOX11 is a proto-oncogene, which is silent in normal mature T-cells, while being aberrantly activated in T-cell acute lymphoblastic leukaemia (T-ALL) by translocations t(10;14)(q24;q11) or t(7;10)(q35;q24). Although many oncogenes are expressed in alternative forms in cancer, thus far, only one form of the human HOX11 transcript has been reported. We describe here the identification of three alternative transcripts of the HOX11 proto-oncogene, expressed in primary T-ALL specimens. Using rapid amplification of cDNA ends (RACE) and targeted RT-PCR, we have sequenced 23 individual cDNA clones characterising these novel transcripts. Northern hybridisation identified particular novel exons expressed in T-ALL, which are not expressed in normal T-cells. To date, aberrant expression of HOX11 has only been associated with leukaemia. Our survey of a range of neuroblastoma and primitive neuroectodermal tumour (PNET) cell lines demonstrated the expression of these novel HOX11 transcripts in tumours of neural origin, while their expression was not detected in normal brain tissues. Strikingly, the dominant transcript in these neural tumour cell lines is more than 1 kb larger than the dominant transcript in T-ALL. These observations, combined with sequence data from several EST clones derived from medulloblastoma cDNA libraries, support a new hypothesis that HOX11 may also function as a neural oncogene or brain tumour marker.