Expression of myeloid-specific genes in childhood acute lymphoblastic leukemia - a cDNA array study

Prognostic significance of neutrophil extracellular trap-related genes in childhood acute lymphoblastic leukemia: insights from multi-omics and in vitro experiment

BACKGROUND

This study aimed to develop a prognostic model based on extracellular trap-related genes (NETRGs) for patients with cALL.

METHODS

Data from the TARGET-ALL-P2 and TARGET-ALL-P3 cohorts in the Genomic Data Commons database, the transcriptome dataset GSE26713, the single-cell transcriptome dataset GSE130116 from the Gene Expression Omnibus database and 306 NETRGs identified were analysed. Differentially expressed genes (DEGs) were identified from GSE26713 and differentially expressed NETRGs (DE-NETRGs) were obtained by overlapping DEGs with NETRGs. Functional analyses were conducted. Key feature genes were identified through univariate and least absolute shrinkage and selection operator (LASSO) regression. Prognostic genes were determined via multivariate Cox regression analysis, followed by the construction and validation of a risk model and nomogram. Additional analyses included immune profiling, drug sensitivity, functional differences, cell-type-specific expression, enrichment analysis and RT-qPCR.

RESULTS

A total of 1,270 DEGs were identified in GSE26713, of which 74 overlapped with NETRGs. Seven prognostic genes were identified using univariate, LASSO and multivariate Cox regression analyses. Survival analysis revealed lower survival rates in the high-risk group. Independent prognostic analysis identified risk scores and primary diagnosis as independent predictors of prognosis. Immune cell profiling showed significant differences in cell populations such as aDCs, eosinophils and Th2 cells between risk groups. Six cell subtypes were annotated, with prognostic genes predominantly expressed in myeloid cells. RT-qPCR revealed that PTAFR, FCGR2A, RETN and CAT were significantly downregulated, while TLR2 and S100A12 were upregulated in cALL.

CONCLUSION

TLR2, PTAFR, FCGR2A, RETN, S100A12 and CAT may serve as potential therapeutic targets.

Bioinformatics analysis and identification of hub genes and immune-related molecular mechanisms in chronic myeloid leukemia

BACKGROUND

Chronic myeloid leukemia (CML) is a malignant hyperplastic tumor of the bone marrow originating from pluripotent hematopoietic stem cells. The advent of tyrosine kinase inhibitors (TKIs) has greatly improved the survival rate of patients with CML. However, TKI-resistance leads to the disease recurrence and progression. This study aimed to identify immune-related genes (IRGs) associated with CML progression.

METHODS

We extracted the gene's expression profiles from the Gene Expression Omnibus (GEO). Bioinformatics analysis was used to determine the differentially expressed IRGs of CML and normal peripheral blood mononuclear cells (PBMCs). Functional enrichment and gene set enrichment analysis (GSEA) were used to explore its potential mechanism. Hub genes were identified using Molecular Complex Detection (MCODE) and the CytoHubba plugin. The hub genes' diagnostic value was evaluated using the receiver operating characteristic (ROC). The relative proportions of infiltrating immune cells in each CML sample were evaluated using CIBERSORT. Quantitative real-time PCR (RT-qPCR) was used to validate the hub gene expression in clinical samples.

RESULTS

A total of 31 differentially expressed IRGs were identified. GO analyses revealed that the modules were typically enriched in the receptor ligand activity, cytokine activity, and endopeptidase activity. KEGG enrichment analysis of IRGs revealed that CML involved Th17 cell differentiation, the NF-kappa B signaling pathway, and cytokine-cytokine receptor interaction. A total of 10 hub genes were selected using the PPI network. GSEA showed that these hub genes were related to the gamma-interferon immune response, inflammatory response, and allograft rejection. ROC curve analysis suggested that six hub genes may be potential biomarkers for CML diagnosis. Further analysis indicated that immune cells were associated with the pathogenesis of CML. The RT-qPCR results showed that proteinase 3 (PRTN3), cathepsin G (CTSG), matrix metalloproteinase 9 (MMP9), resistin (RETN), eosinophil derived neurotoxin (RNase2), eosinophil cationic protein (ECP, RNase3) were significantly elevated in CML patients' PBMCs compared with healthy controls.

CONCLUSION

These results improved our understanding of the functional characteristics and immune-related molecular mechanisms involved in CML progression and provided potential diagnostic biomarkers and therapeutic targets.

Identification of a three-gene-based prognostic model in multiple myeloma using bioinformatics analysis

Background

Multiple myeloma (MM), the second most hematological malignancy, has high incidence and remains incurable till now. The pathogenesis of MM is poorly understood. This study aimed to identify novel prognostic model for MM on gene expression profiles.

Methods

Gene expression datas of MM (GSE6477, GSE136337) were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in GSE6477 between case samples and normal control samples were screened by the limma package. Meanwhile, enrichment analysis was conducted, and a protein-protein interaction (PPI) network of these DEGs was established by STRING and cytoscape software. Co-expression modules of genes were built by Weighted Correlation Network Analysis (WGCNA). Key genes were identified both from hub genes and the DEGs. Univariate and multivariate Cox congression were performed to screen independent prognostic genes to construct a predictive model. The predictive power of the model was evaluated by Kaplan–Meier curve and time-dependent receiver operating characteristic (ROC) curves. Finally, univariate and multivariate Cox regression analyse were used to investigate whether the prognostic model could be independent of other clinical parameters.

Results

GSE6477, including 101 case and 15 normal control, were screened as the datasets. A total of 178 DEGs were identified, including 59 up-regulated and 119 down-regulated genes. In WGCNA analysis, module black and module purple were the most relevant modules with cancer traits, and 92 hub genes in these two modules were selected for further analysis. Next, 47 genes were chosen both from the DEGs and hub genes as key genes. Three genes (LYVE1, RNASE1, and RNASE2) were finally screened by univariate and multivariate Cox regression analyses and used to construct a risk model. In addition, the three-gene prognostic model revealed independent and accurate prognostic capacity in relation to other clinical parameters for MM patients.

Conclusion

In summary, we identified and constructed a three-gene-based prognostic model that could be used to predict overall survival of MM patients.

A signature of seven immune-related genes predicts overall survival in male gastric cancer patients

Background

Gastric cancer (GC) has a high mortality rate and is one of the most fatal malignant tumours. Male sex has been proven as an independent risk factor for GC. This study aimed to identify immune-related genes (IRGs) associated with the prognosis of male GC.

Methods

RNA sequencing and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed IRGs between male GC and normal tissues were identified by integrated bioinformatics analysis. Univariate and multivariate Cox regression analyses were applied to screen survival-associated IRGs. Then, GC patients were separated into high- and low-risk groups based on the median risk score. Furthermore, a nomogram was constructed based on the TCGA dataset. The prognostic value of the risk signature model was evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell’s concordance index and calibration curves. In addition, the gene expression dataset from the Gene Expression Omnibus (GEO) was also downloaded for external validation. The relative proportions of 22 types of infiltrating immune cells in each male GC sample were evaluated using CIBERSORT.

Results

A total of 276 differentially expressed IRGs were screened, including 189 up-regulated and 87 down-regulated genes. Subsequently, a seven-IRGs signature (LCN12, CCL21, RNASE2, CGB5, NRG4, AGTR1 and NPR3) was identified to be significantly associated with the overall survival (OS) of male GC patients. Survival analysis indicated that patients in the high-risk group exhibited a poor clinical outcome. The results of multivariate analysis revealed that the risk score was an independent prognostic factor. The established nomogram could be used to evaluate the prognosis of individual male GC patients. Further analysis showed that the prognostic model had excellent predictive performance in both TCGA and validated cohorts. Besides, the results of tumour-infiltrating immune cell analysis indicated that the seven-IRGs signature could reflect the status of the tumour immune microenvironment.

Conclusions

Our study developed a novel seven-IRGs risk signature for individualized survival prediction of male GC patients.

Development and validation of a prognostic model for kidney renal clear cell carcinoma based on RNA binding protein expression

Dysregulated expression of RNA-binding proteins (RBPs) is strongly associated with the development and progression of multiple tumors. However, little is known about the role of RBPs in kidney renal clear cell carcinoma (KIRC). In this study, we examined RBP expression profiles using The Cancer Genome Atlas database and identified 133 RBPs that were differentially expressed in KIRC and non-tumor tissues. We then systematically analyzed the potential biological functions of these RBPs and established PPIs. Based on Lasso regression and Cox survival analyses, we constructed a risk model that could independently and accurately predict prognosis based on seven RBPs (NOL12, PABPC1L, RNASE2, RPL22L1, RBM47, OASL, and YBX3). Survival times were shorter in patients with high risk scores for cohorts stratified by different characteristics. Gene set enrichment analysis was also performed to further understand functional differences between high- and low-risk groups. Finally, we developed a clinical nomogram with a concordance index of 0.792 for estimating 3- and 5-year survival probabilities. Our results demonstrate that this risk model could potentially improve individualized diagnostic and therapeutic strategies.

Identification of gene modules associated with survival of diffuse large B-cell lymphoma treated with CHOP-based chemotherapy

Diffuse Large B-cell Lymphoma (DLBCL), a heterogeneous disease, is influenced by complex network of gene interactions. Most previous studies focused on individual genes, but ignored the importance of intergenic correlations. In current study, we aimed to explore the association between gene networks and overall survival (OS) of DLBCL patients treated with CHOP-based chemotherapy (cyclophosphamide combination with doxorubicin, vincristine and prednisone). Weighted gene co-expression network analysis was conducted to obtain insights into the molecular characteristics of DLBCL. Ten co-expression gene networks (modules) were identified in training dataset (n = 470), and their associations with patients' OS after chemotherapy were tested. The results were validated in four independent datasets (n = 802). Gene ontology (GO) biological function enrichment analysis was conducted with Metascape. Three modules (purple, brown and red), which were enriched in T-cell immune, cell-cell adhesion and extracellular matrix (ECM), respectively, were found to be related to longer OS. Higher expression of several hub genes within these three co-expression modules, for example, LCP2 (HR = 0.77, p = 5.40 × 10^-2), CD2 (HR = 0.87, p = 6.31 × 10^-2), CD3D (HR = 0.83, p = 6.94 × 10^-3), FYB (HR = 0.82, p = 1.40 × 10^-2), GZMK (HR = 0.92, p = 1.19 × 10^-1), FN1 (HR = 0.88, p = 7.06 × 10^-2), SPARC (HR = 0.82, p = 2.06 × 10^-2), were found to be associated with favourable survival. Moreover, the associations of the modules and hub genes with OS in different molecular subtypes and different chemotherapy groups were also revealed. In general, our research revealed the key gene modules and several hub genes were upregulated correlated with good survival of DLBCL patients, which might provide potential therapeutic targets for future clinical research.

Addiction to Runx1 is partially attenuated by loss of p53 in the Eµ-Myc lymphoma model

The Runx genes function as dominant oncogenes that collaborate potently with Myc or loss of p53 to induce lymphoma when over-expressed. Here we examined the requirement for basal Runx1 activity for tumor maintenance in the Eμ-Myc model of Burkitt's lymphoma. While normal Runx1^fl/fl lymphoid cells permit mono-allelic deletion, primary Eμ-Myc lymphomas showed selection for retention of both alleles and attempts to enforce deletion in vivo led to compensatory expansion of p53^null blasts retaining Runx1. Surprisingly, Runx1 could be excised completely from established Eμ-Myc lymphoma cell lines in vitro without obvious effects on cell phenotype. Established lines lacked functional p53, and were sensitive to death induced by introduction of a temperature-sensitive p53 (Val135) allele. Transcriptome analysis of Runx1-deleted cells revealed a gene signature associated with lymphoid proliferation, survival and differentiation, and included strong de-repression of recombination-activating (Rag) genes, an observation that was mirrored in a panel of human acute leukemias where RUNX1 and RAG1,2 mRNA expression were negatively correlated. Notably, despite their continued growth and tumorigenic potential, Runx1^null lymphoma cells displayed impaired proliferation and markedly increased sensitivity to DNA damage and dexamethasone-induced apoptosis, validating Runx1 function as a potential therapeutic target in Myc-driven lymphomas regardless of their p53 status.

The RUNX Genes as Conditional Oncogenes: Insights from Retroviral Targeting and Mouse Models

The observation that the Runx genes act as targets for transcriptional activation by retroviral insertion identified a new family of dominant oncogenes. However, it is now clear that Runx genes are 'conditional' oncogenes whose over-expression is growth inhibitory unless accompanied by another event such as concomitant over-expression of MYC or loss of p53 function. Remarkably, while the oncogenic activities of either MYC or RUNX over-expression are suppressed while p53 is intact, the combination of both neutralises p53 tumour suppression in vivo by as yet unknown mechanisms. Moreover, there is emerging evidence that endogenous, basal RUNX activity is important to maintain the viability and proliferation of MYC-driven lymphoma cells. There is also growing evidence that the human RUNX genes play a similar conditional oncogenic role and are selected for over-expression in end-stage cancers of multiple types. Paradoxically, reduced RUNX activity can also predispose to cell immortalisation and transformation, particularly by mutant Ras. These apparently conflicting observations may be reconciled in a stage-specific model of RUNX involvement in cancer. A question that has yet to be fully addressed is the extent to which the three Runx genes are functionally redundant in cancer promotion and suppression.

Internal tandem duplication of FLT3 deregulates proliferation and differentiation and confers resistance to the FLT3 inhibitor AC220 by Up-regulating RUNX1 expression in hematopoietic cells

Internal tandem duplication in the FLT3 gene (FLT3/ITD), which is found in patients with acute myeloid leukemia (AML), causes resistance to FLT3 inhibitors. We found that RUNX1, a transcription factor that regulates normal hematopoiesis, is up-regulated in patients with FLT3/ITD(+) AML. While RUNX1 can function as a tumor suppressor, recent data have shown that RUNX1 is required for AML cell survival. In the present study, we investigated the functional role of RUNX1 in FLT3/ITD signaling. FLT3/ITD induced growth factor-independent proliferation and impaired G-CSF mediated myeloid differentiation in 32D hematopoietic cells, coincident with up-regulation of RUNX1 expression. Silencing of RUNX1 expression significantly decreased proliferation and secondary colony formation, and partially abrogated the impaired myeloid differentiation of FLT3/ITD(+) 32D cells. Although the number of FLT3/ITD(+) 32D cells declined after incubation with the FLT3/ITD inhibitor AC220, the cells became refractory to AC220, concomitant with up-regulation of RUNX1. Silencing of RUNX1 abrogated the emergence and proliferation of AC220-resistant FLT3/ITD(+) 32D cells in the presence of AC220. Our data indicate that FLT3/ITD deregulates cell proliferation and differentiation and confers resistance to AC220 by up-regulating RUNX1 expression. These findings suggest an oncogenic role for RUNX1 in FLT3/ITD(+) cells and that inhibition of RUNX1 function represents a potential therapeutic strategy in patients with refractory FLT3/ITD(+) AML.

The Human Antimicrobial Protein Calgranulin C Participates in Control of Helicobacter pylori Growth and Regulation of Virulence

During infectious processes, antimicrobial proteins are produced by both epithelial cells and innate immune cells. Some of these antimicrobial molecules function by targeting transition metals and sequestering these metals in a process referred to as "nutritional immunity." This chelation strategy ultimately starves invading pathogens, limiting their growth within the vertebrate host. Recent evidence suggests that these metal-binding antimicrobial molecules have the capacity to affect bacterial virulence, including toxin secretion systems. Our previous work showed that the S100A8/S100A9 heterodimer (calprotectin, or calgranulin A/B) binds zinc and represses the elaboration of the H. pylori cag type IV secretion system (T4SS). However, there are several other S100 proteins that are produced in response to infection. We hypothesized that the zinc-binding protein S100A12 (calgranulin C) is induced in response to H. pylori infection and also plays a role in controlling H. pylori growth and virulence. To test this, we analyzed gastric biopsy specimens from H. pylori-positive and -negative patients for S100A12 expression. These assays showed that S100A12 is induced in response to H. pylori infection and inhibits bacterial growth and viability in vitro by binding nutrient zinc. Furthermore, the data establish that the zinc-binding activity of the S100A12 protein represses the activity of the cag T4SS, as evidenced by the gastric cell "hummingbird" phenotype, interleukin 8 (IL-8) secretion, and CagA translocation assays. In addition, high-resolution field emission gun scanning electron microscopy (FEG-SEM) was used to demonstrate that S100A12 represses biogenesis of the cag T4SS. Together with our previous work, these data reveal that multiple S100 proteins can repress the elaboration of an oncogenic bacterial surface organelle.

RUNX1 is a key target in t(4;11) leukemias that contributes to gene activation through an AF4-MLL complex interaction

The Mixed Lineage Leukemia (MLL) protein is an important epigenetic regulator required for the maintenance of gene activation during development. MLL chromosomal translocations produce novel fusion proteins that cause aggressive leukemias in humans. Individual MLL fusion proteins have distinct leukemic phenotypes even when expressed in the same cell type, but how this distinction is delineated on a molecular level is poorly understood. Here, we highlight a unique molecular mechanism whereby the RUNX1 gene is directly activated by MLL-AF4 and the RUNX1 protein interacts with the product of the reciprocal AF4-MLL translocation. These results support a mechanism of transformation whereby two oncogenic fusion proteins cooperate by activating a target gene and then modulating the function of its downstream product.

Analysis of select members of the E26 (ETS) transcription factors family in colorectal cancer

The E-twenty-six (ETS) family of transcription factors is known to act as positive or negative regulators of the expression of genes that are involved in diverse biological processes, including those that control cellular proliferation, differentiation, hematopoiesis, apoptosis, metastasis, tissue remodeling, and angiogenesis. Identification of target gene promoters of normal and oncogenic transcription factors provides new insights into the regulation of genes that are involved in the control of normal cell growth and differentiation. The aim of the present investigation was to analyze the differential expression of 11 ETS (ELF-3, ESE3, ETS1, ETV3, ETV4, ETV6, NERF, PDEF, PU1, Spi-B, and Spi-C) as potential markers for prognostic of colorectal cancer. A series of paired tissue biopsies consisting of a tumor and a non-affected control sample were harvested from 28 individuals suffering from diagnosed colorectal lesions. Total RNA was isolated from the samples, and after reverse transcription, differential expression of the select ETS was carried out through real-time polymerase chain reaction. Tumor staging as determined by histopathology was carried out to correlate the degree of tumor invasiveness with the expression of the ETS genes. The results demonstrated a different quantitative profile of expression in tumors and normal tissues. ETV4 was significantly upregulated with further increase in the event of lymph node involvement. PDEF and Spi-B presented downregulation, which was more significant when lymph node involvement was present. These findings were supported by immunohistochemistry of tumoral tissues. The results suggest that select ETS may serve as potential markers of colorectal cancer invasiveness and metastasis.

Runx1 promotes B-cell survival and lymphoma development

Runx1 is essential for the homeostatic control of normal hematopoiesis and is required for lymphoid development. Translocations or point mutations that result in RUNX1 loss or disrupted function predispose to leukemia but data derived from model systems suggests that Runx genes can also be pro-oncogenic. Here we investigate the effects of enforced Runx1 expression in lymphoid lineages both in vivo and in vitro and show that transgene expression enhanced cell survival in the thymus and bone marrow but strongly inhibited the expansion of hematopoietic and B cell progenitors in vitro. Despite this, modestly enhanced levels of Runx1 accelerated Myc-induced lymphomagenesis in both the B cell and T cell lineages. Together these data provide formal proof that wild type Runx1 can promote oncogenesis in lymphoid tissues and that, in addition to loss of function, gain of function may have an aetiological role in leukemia.

Cited2 is required for normal hematopoiesis in the murine fetal liver

Cited2 (cAMP-responsive elementbinding protein [CBP]/p300-interacting transactivators with glutamic acid [E] and aspartic acid [D]-rich tail 2) is a newly identified transcriptional modulator. Knockout of the Cited2 gene results in embryonic lethality with embryos manifesting heart and neural tube defects. Cited2-/- fetal liver displayed significant reduction in the numbers of Lin(-)c-Kit+Sca-1+ cells, Lin(-)c-Kit+ cells, and progenitor cells of different lineages. Fetal liver cells from Cited2-/- embryos gave rise to markedly reduced number of colonies in the colony-forming unit assay. Primary and secondary transplantation studies showed significantly compromised reconstitution of T-lymphoid, B-lymphoid, and myeloid lineages in mice that received a transplant of Cited2-/- fetal liver cells. Competitive reconstitution experiments further showed that fetal liver hematopoietic stem cell (HSC) function is severely impaired due to Cited2 deficiency. Microarray analysis showed decreased expression of Wnt5a and a panel of myeloid molecular markers such as PRTN3, MPO, Neutrophil elastase, Cathepsin G, and Eosinophil peroxidase in Cited2-/- fetal livers. Decreased expression of Bmi-1, Notch1, LEF-1, Mcl-1, and GATA2 was also observed in Cited2-/- Lin(-)c-Kit+ cells. The present study uncovers for the first time a novel role of Cited2 in the maintenance of hematopoietic homeostasis during embryogenesis and thus provides new insights into the molecular regulation of hematopoietic development.

Multiple gene expression classifiers from different array platforms predict poor prognosis of colorectal cancer

PURPOSE

This study aimed to develop gene classifiers to predict colorectal cancer recurrence. We investigated whether gene classifiers derived from two tumor series using different array platforms could be independently validated by application to the alternate series of patients.

EXPERIMENTAL DESIGN

Colorectal tumors from New Zealand (n = 149) and Germany (n = 55) patients had a minimum follow-up of 5 years. RNA was profiled using oligonucleotide printed microarrays (New Zealand samples) and Affymetrix arrays (German samples). Classifiers based on clinical data, gene expression data, and a combination of the two were produced and used to predict recurrence. The use of gene expression information was found to improve the predictive ability in both data sets. The New Zealand and German gene classifiers were cross-validated on the German and New Zealand data sets, respectively, to validate their predictive power. Survival analyses were done to evaluate the ability of the classifiers to predict patient survival.

RESULTS

The prediction rates for the New Zealand and German gene-based classifiers were 77% and 84%, respectively. Despite significant differences in study design and technologies used, both classifiers retained prognostic power when applied to the alternate series of patients. Survival analyses showed that both classifiers gave a better stratification of patients than the traditional clinical staging. One classifier contained genes associated with cancer progression, whereas the other had a large immune response gene cluster concordant with the role of a host immune response in modulating colorectal cancer outcome.

CONCLUSIONS

The successful reciprocal validation of gene-based classifiers on different patient cohorts and technology platforms supports the power of microarray technology for individualized outcome prediction of colorectal cancer patients. Furthermore, many of the genes identified have known biological functions congruent with the predicted outcomes.

The chemosensitivity to therapy of childhood early B acute lymphoblastic leukemia could be determined by the combined expression of CD34, SPI-B and BCR genes

We have identified genes differentially expressed in childhood early B acute lymphoblastic leukemia at diagnosis, according to chemosensitivity. Chemosensitive (M1) and chemoresistant (M3) patients present <5% and >25% of residual leukemic blasts at 21 days of treatment, respectively. The expression profiles of 4205 genes for 32 patients included in the FRALLE93 protocol have been determined using microarray. From differential analysis, CD34, SPI-B and BCR distinguished M1 from M3 patients using microarray and RT-PCR data. Linear discriminant analysis (LDA) and cross-validation show that the combined expression of these three genes classify and predict correctly around 90% and 80% of patients, respectively.

Gene expression profiling data in lymphoma and leukemia: review of the literature and extrapolation of pertinent clinical applications

CONTEXT

Gene expression (GE) analyses using microarrays have become an important part of biomedical and clinical research in hematolymphoid malignancies. However, the methods are time-consuming and costly for routine clinical practice.

OBJECTIVES

To review the literature regarding GE data that may provide important information regarding pathogenesis and that may be extrapolated for use in diagnosing and prognosticating lymphomas and leukemias; to present GE findings in Hodgkin and non-Hodgkin lymphomas, acute leukemias, and chronic myeloid leukemia in detail; and to summarize the practical clinical applications in tables that are referenced throughout the text.

DATA SOURCE

PubMed was searched for pertinent literature from 1993 to 2005.

CONCLUSIONS

Gene expression profiling of lymphomas and leukemias aids in the diagnosis and prognostication of these diseases. The extrapolation of these findings to more timely, efficient, and cost-effective methods, such as flow cytometry and immunohistochemistry, results in better diagnostic tools to manage the diseases. Flow cytometric and immunohistochemical applications of the information gained from GE profiling assist in the management of chronic lymphocytic leukemia, other low-grade B-cell non-Hodgkin lymphomas and leukemias, diffuse large B-cell lymphoma, nodular lymphocyte-predominant Hodgkin lymphoma, and classic Hodgkin lymphoma. For practical clinical use, GE profiling of precursor B acute lymphoblastic leukemia, precursor T acute lymphoblastic leukemia, and acute myeloid leukemia has supported most of the information that has been obtained by cytogenetic and molecular studies (except for the identification of FLT3 mutations for molecular analysis), but extrapolation of the analyses leaves much to be gained based on the GE profiling data.

The RUNX genes: gain or loss of function in cancer

The RUNX genes have come to prominence recently because of their roles as essential regulators of cell fate in development and their paradoxical effects in cancer, in which they can function either as tumour-suppressor genes or dominant oncogenes according to context. How can this family of transcription factors have such an ambiguous role in cancer? How and where do these genes impinge on the pathways that regulate growth control and differentiation? And what is the evidence for a wider role for the RUNX genes in non-haematopoietic cancers?

Differentially expressed genes in nonsmall cell lung cancer: expression profiling of cancer-related genes in squamous cell lung cancer

The expression patterns of cancer-related genes in 13 cases of squamous cell lung cancer (SCC) were characterized and compared with those in normal lung tissue and 13 adenocarcinomas (AC), the other major type of nonsmall cell lung cancer (NSCLC). cDNA array was used to screen the gene expression levels and the array results were verified using a real-time reverse-transcriptase-polymerase chain reaction (RT-PCR). Thirty-nine percent of the 25 most upregulated and the 25 most downregulated genes were common to SCC and AC. Of these genes, DSP, HMGA1 (alias HMGIY), TIMP1, MIF, CCNB1, TN, MMP11, and MMP12 were upregulated and COPEB (alias CPBP), TYROBP, BENE, BMPR2, SOCS3, TIMP3, CAV1, and CAV2 were downregulated. The expression levels of several genes from distinct protein families (cytokeratins and hemidesmosomal proteins) were markedly increased in SCC compared with AC and normal lung. In addition, several genes, overexpressed in SCC, such as HMGA1, CDK4, IGFBP3, MMP9, MMP11, MMP12, and MMP14, fell into distinct chromosomal loci, which we have detected as gained regions on the basis of comparative genomic hybridization data. Our study revealed new candidate genes involved in NSCLC.

ESE-1 is a novel transcriptional mediator of angiopoietin-1 expression in the setting of inflammation

Angiogenesis is a critical component of the inflammatory response associated with a number of conditions. Angiopoietin-1 (Ang-1) is an angiogenic growth factor that promotes the chemotaxis of endothelial cells and facilitates the maturation of new blood vessels. Ang-1 expression is up-regulated in response to tumor necrosis factor-alpha (TNF-alpha). To begin to elucidate the underlying molecular mechanisms by which Ang-1 gene expression is regulated during inflammation, we isolated 3.2 kb of the Ang-1 promoter that contain regulatory elements sufficient to mediate induction of the promoter in response to TNF-alpha, interleukin-1beta, and endotoxin. Surprisingly, sequence analysis of this promoter failed to reveal binding sites for transcription factors that are frequently associated with mediating inflammatory responses, such as NF-kappaB, STAT, NFAT, or C/EBP. However, putative binding sites for ETS and AP-1 transcription factor family members were identified. Interestingly, among a panel of ETS factors tested in a transient transfection assay, only the ETS factor ESE-1 was capable of transactivating the Ang-1 promoter. ESE-1 binds to specific ETS sites within the Ang-1 promoter that are functionally important for transactivation by ESE-1. ESE-1 and Ang-1 are induced in synovial fibroblasts in response to inflammatory cytokines, with ESE-1 induction slightly preceding that of Ang-1. Mutation of a high-affinity ESE-1 binding site leads to a marked reduction in Ang-1 transactivation by ESE-1, inducibility by inflammatory cytokines, and DNA binding to the ESE-1 protein. Transcriptional profiling of cells transiently transfected with an ESE-1 expression vector demonstrates that the endogenous Ang-1 gene is directly inducible by ESE-1. Finally, Ang-1 and ESE-1 exhibit a similar and strong expression pattern in the synovium of patients with rheumatoid arthritis. Our results support a novel paradigm for the ETS factor ESE-1 as a transcriptional mediator of angiogenesis in the setting of inflammation.

Aberrant expression of HOXA9, DEK, CBL and CSF1R in acute myeloid leukemia

Previous gene function analyses have indicated that HOXA9, DEK, CBL and CSF1R are aberrantly expressed in acute myeloid leukemia (AML). We analyzed the expression of these genes in a series of 41 adult patients with AML using quantitative real-time RT-PCR, and tested the association of the expression with the following hematologic and clinical parameters: age, FAB, immunophenotype and karyotype aberrations. A high proportion of the patients showed over- or underexpression of the analyzed genes. DEK was overexpressed in 98% of the cases, whereas CBL, CSF1R and HOXA9 were either overexpressed in 20%, 17% and 78% or underexpressed in 20%, 42% and 15% of the cases, respectively. Patients whose karyotype contained t(8;21)(q22;q22), showed lower relative expression of HOXA9 at a statistically significant level (p < 0.05). Bone marrow samples without expression of CD34 antigen were associated with either overexpression of DEK or HOXA9. Furthermore, an association was found between the AML-M2 subtype and lower expression of CBL, CSF1R or HOXA9, and between the AML-M5 subtype and CBL or CSF1R overexpression.