Routine expression profiling of microarray gene signatures in acute leukaemia by real-time PCR of human bone marrow

RBBP4: A novel diagnostic and prognostic biomarker for non-small-cell lung cancer correlated with autophagic cell death

BACKGROUND

Non-small-cell lung cancer (NSCLC) often presents at later stages, typically associated with poor prognosis. Autophagy genes play a role in the progression of tumors. This study investigated the clinical relevance, prognostic value, and biological significance of RBBP4 in NSCLC.

METHODS

We assessed RBBP4 expression using the GSE30219 and TCGA NSCLC datasets and NSCLC cells, exploring its links with clinical outcomes, tumor immunity, and autophagy genes through bioinformatics analysis after transcriptome sequencing of RBBP4-knockdown and control PC9 cells. We identified differentially expressed genes (DEGs) and conducted Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and protein-protein interaction network analyses. The significance of autophagy-related DEGs was evaluated for diagnosis and prognosis using the GSE30219 dataset. Experiments both in vivo and in vitro explored the biological mechanisms behind RBBP4-mediated autophagic cell death in NSCLC.

RESULTS

RBBP4 overexpression in NSCLC correlates with a poorer prognosis. Eighteen types of immune cell were significantly enriched in cultures that had low RBBP4 expression compared high expression. DEGs associated with RBBP4 are enriched in autophagy pathways. Transcriptomic profiling of the PC9 cell line identified autophagy-related DEGs associated with RBBP4 that exhibited differential expression in NSCLC, suggesting prognostic applications. In vitro experiments demonstrated that RBBP4 knockdown induced autophagy and apoptosis in PC9 cells, promoting cell death, which was inhibited by 3-MA. In vivo, targeted siRNA against RBBP4 significantly reduced tumor development in PC9 cell-injected nude mice, elevating autophagy-related protein levels and inducing apoptosis and necrosis in tumor tissues.

CONCLUSION

In NSCLC, RBBP4 upregulation correlates with poor prognosis and altered immunity. Its knockdown induces autophagic cell death in NSCLC cells. These results indicate RBBP4 as a potential NSCLC diagnostic marker and its autophagy modulation as a prospective therapeutic target.

Unveiling the molecular structure and role of RBBP4/7: implications for epigenetic regulation and cancer research

Retinoblastoma-binding protein (RBBP) family is a class of proteins that can interact with tumor suppressor retinoblastoma protein (pRb). RBBP4 and RBBP7 are the only pair of homologous proteins in this family, serving as scaffold proteins whose main function is to offer a platform to indirectly connect two proteins. This characteristic allows them to extensively participate in the binding of various proteins and epigenetic complexes, indirectly influencing the function of effector proteins. As a result, they are often highlighted in organism activities involving active epigenetic modifications, such as embryonic development and cancer activation. In this review, we summarize the structural characteristics of RBBP4/7, the complexes they are involved in, their roles in embryonic development and cancer, as well as potential future research directions, which we hope to inspire the field of epigenetic research in the future.

Functional characterization of RebL1 highlights the evolutionary conservation of oncogenic activities of the RBBP4/7 orthologue in Tetrahymena thermophila

Retinoblastoma-binding proteins 4 and 7 (RBBP4 and RBBP7) are two highly homologous human histone chaperones. They function in epigenetic regulation as subunits of multiple chromatin-related complexes and have been implicated in numerous cancers. Due to their overlapping functions, our understanding of RBBP4 and 7, particularly outside of Opisthokonts, has remained limited. Here, we report that in the ciliate protozoan Tetrahymena thermophila a single orthologue of human RBBP4 and 7 proteins, RebL1, physically interacts with histone H4 and functions in multiple epigenetic regulatory pathways. Functional proteomics identified conserved functional links for Tetrahymena RebL1 protein as well as human RBBP4 and 7. We found that putative subunits of multiple chromatin-related complexes including CAF1, Hat1, Rpd3, and MuvB, co-purified with RebL1 during Tetrahymena growth and conjugation. Iterative proteomics analyses revealed that the cell cycle regulatory MuvB-complex in Tetrahymena is composed of at least five subunits including evolutionarily conserved Lin54, Lin9 and RebL1 proteins. Genome-wide analyses indicated that RebL1 and Lin54 (Anqa1) bind within genic and intergenic regions. Moreover, Anqa1 targets primarily promoter regions suggesting a role for Tetrahymena MuvB in transcription regulation. RebL1 depletion inhibited cellular growth and reduced the expression levels of Anqa1 and Lin9. Consistent with observations in glioblastoma tumors, RebL1 depletion suppressed DNA repair protein Rad51 in Tetrahymena, thus underscoring the evolutionarily conserved functions of RBBP4/7 proteins. Our results suggest the essentiality of RebL1 functions in multiple epigenetic regulatory complexes in which it impacts transcription regulation and cellular viability.

Novel biomarkers in cancer: The whole is greater than the sum of its parts

The major issues hampering progress in the treatment of cancer patients are distant metastases and drug resistance to chemotherapy. Metastasis formation is a very complex process, and looking at gene signatures alone is not enough to get deep insight into it. This paper reviews traditional and novel approaches to identify gene signature biomarkers and intratumoural fluid pressure both as a novel way of creating predictive markers and as an obstacle to cancer therapy. Finally recently developed in vitro systems to predict the response of individual patient derived cancer explants to chemotherapy are discussed.

Complement cascade gene expression defines novel prognostic subgroups of acute myeloid leukemia

The involvement of the complement pathway in cancer is supported by a growing body of evidence, and yet its role in acute myeloid leukemia (AML) has not been extensively studied. We examined the expression of 87 genes in the complement, coagulation, and fibrinolysis-proteolytic pathways in 374 cytogenetically normal AML samples and observed that these samples can be divided into subgroups on the basis of complement gene expression. Three complement regulatory genes were linked to poor outcome as individual factors in a multivariate analysis (CFH, CFD, and SERPING1) in multiple cohorts. The combined expression of these genes was significantly associated with poorer overall survival in two cohorts of patients <60 years of age, independent of other factors (p ≤ 0.0004). For patients with an intermediate molecular risk, this three-gene risk marker enabled stratification of patients into prognostic subgroups with survival ranging from 17.4% to 44.1%. Thus, the expression of complement pathway genes is linked to outcome in AML, and a three-gene risk marker may improve the risk assessment of patients.

Cancer subtype discovery and biomarker identification via a new robust network clustering algorithm

In cancer biology, it is very important to understand the phenotypic changes of the patients and discover new cancer subtypes. Recently, microarray-based technologies have shed light on this problem based on gene expression profiles which may contain outliers due to either chemical or electrical reasons. These undiscovered subtypes may be heterogeneous with respect to underlying networks or pathways, and are related with only a few of interdependent biomarkers. This motivates a need for the robust gene expression-based methods capable of discovering such subtypes, elucidating the corresponding network structures and identifying cancer related biomarkers. This study proposes a penalized model-based Student’s t clustering with unconstrained covariance (PMT-UC) to discover cancer subtypes with cluster-specific networks, taking gene dependencies into account and having robustness against outliers. Meanwhile, biomarker identification and network reconstruction are achieved by imposing an adaptive penalty on the means and the inverse scale matrices. The model is fitted via the expectation maximization algorithm utilizing the graphical lasso. Here, a network-based gene selection criterion that identifies biomarkers not as individual genes but as subnetworks is applied. This allows us to implicate low discriminative biomarkers which play a central role in the subnetwork by interconnecting many differentially expressed genes, or have cluster-specific underlying network structures. Experiment results on simulated datasets and one available cancer dataset attest to the effectiveness, robustness of PMT-UC in cancer subtype discovering. Moveover, PMT-UC has the ability to select cancer related biomarkers which have been verified in biochemical or biomedical research and learn the biological significant correlation among genes.

Nucleosome occupancy and gene regulation during tumorigenesis

Nucleosomes are the basic structural units of eukaryotic chromatin. In recent years, it has become evident that nucleosomes and their position, in concert with other epigenetic mechanisms (such as DNA methylation, histone modifications, changes in histone variants, as well as small noncoding regulatory RNAs) play essential roles in the control of gene expression. Here, we discuss the mechanisms and factors that regulate nucleosome position and gene expression in normal and cancer cells.

Biomarker identification and cancer classification based on microarray data using Laplace naive Bayes model with mean shrinkage

Biomarker identification and cancer classification are two closely related problems. In gene expression data sets, the correlation between genes can be high when they share the same biological pathway. Moreover, the gene expression data sets may contain outliers due to either chemical or electrical reasons. A good gene selection method should take group effects into account and be robust to outliers. In this paper, we propose a Laplace naive Bayes model with mean shrinkage (LNB-MS). The Laplace distribution instead of the normal distribution is used as the conditional distribution of the samples for the reasons that it is less sensitive to outliers and has been applied in many fields. The key technique is the L1 penalty imposed on the mean of each class to achieve automatic feature selection. The objective function of the proposed model is a piecewise linear function with respect to the mean of each class, of which the optimal value can be evaluated at the breakpoints simply. An efficient algorithm is designed to estimate the parameters in the model. A new strategy that uses the number of selected features to control the regularization parameter is introduced. Experimental results on simulated data sets and 17 publicly available cancer data sets attest to the accuracy, sparsity, efficiency, and robustness of the proposed algorithm. Many biomarkers identified with our method have been verified in biochemical or biomedical research. The analysis of biological and functional correlation of the genes based on Gene Ontology (GO) terms shows that the proposed method guarantees the selection of highly correlated genes simultaneously

A rapid culture technique produces functional dendritic-like cells from human acute myeloid leukemia cell lines

Most anti-cancer immunotherapeutic strategies involving dendritic cells (DC) as vaccines rely upon the adoptive transfer of DC loaded with exogenous tumour-peptides. This study utilized human acute myeloid leukemia (AML) cells as progenitors from which functional dendritic-like antigen presenting cells (DLC) were generated, that constitutively express tumour antigens for recognition by CD8⁺ T cells. DLC were generated from AML cell lines KG-1 and MUTZ-3 using rapid culture techniques and appropriate cytokines. DLC were evaluated for their cell-surface phenotype, antigen uptake and ability to stimulate allogeneic responder cell proliferation, and production of IFN-γ; compared with DC derived from normal human PBMC donors. KG-1 and MUTZ-3 DLC increased expression of CD80, CD83, CD86, and HLA-DR, and MUTZ-3 DLC downregulated CD14 and expressed CD1a. Importantly, both KG-1 and MUTZ-3-derived DLC promoted proliferation of allogeneic responder cells more efficiently than unmodified cells; neither cells incorporated FITC-labeled dextran, but both stimulated IFN-γ production from responding allogeneic CD8⁺ T cells. Control DC produced from PBMC using the FastDC culture also expressed high levels of critical cell surface ligands and demonstrated good APC function. This paper indicates that functional DLC can be cultured from the AML cell lines KG-1 and MUTZ-3, and FastDC culture generates functional KG-1 DLC.

Poly(A) RT-PCR measurement of diagnostic genes in pancreatic juice in pancreatic cancer

Background:

The last decade has seen significant progress in understanding the molecular biology of pancreatic adenocarcinoma. There is now an urgent need to translate these molecular techniques to clinical practice in order to improve diagnosis and prediction of response to treatment. The objectives of this study are to utilise poly(A) RT–PCR to measure expression levels of diagnostic Indicator genes, selected from microarray studies, of RNA from intraoperatively sampled pancreatic ductal juice and to correlate these expression levels with those in matched pancreatic tissue resection samples.

Methods:

Intraoperative sampling of pancreatic juice and collection of matched tissue samples was undertaken in patients undergoing pancreaticoduodenectomy for suspected tumour. RNA was isolated and poly(A) PCR and real-time PCR used to measure expression levels of 30 genes. Spearman's rank correlation test was used to examine the relationship of gene expression between pancreatic juice and tissue.

Results:

Of the 30 Indicator genes measured, just one, ANXA1, showed a significant correlation of expression level between pancreatic juice and tissue samples, whereas three genes, IGFBP3 (P⩽0.035), PSCA (P⩽0.001) and SPINK1 (P⩽0.05), showed significantly different expression between cancerous and benign pancreatic tissue samples.

Conclusions:

These results demonstrate that RNA analysis of pancreatic juice is feasible using the poly(A) cDNA technique, that correlation of gene expression exists between pancreatic juice and tissue for very few genes and that gene expression profiling can distinguish between benign and malignant pancreatic tissue. This indicates possible use of the technique for measurement of Indicator genes in pancreatic tissue for diagnosis of pancreatic cancer from very small tissue samples.

microRNA profiling in Epstein-Barr virus-associated B-cell lymphoma

The Epstein–Barr virus (EBV) is an oncogenic human Herpes virus found in ∼15% of diffuse large B-cell lymphoma (DLBCL). EBV encodes miRNAs and induces changes in the cellular miRNA profile of infected cells. MiRNAs are small, non-coding RNAs of ∼19–26 nt which suppress protein synthesis by inducing translational arrest or mRNA degradation. Here, we report a comprehensive miRNA-profiling study and show that hsa-miR-424, -223, -199a-3p, -199a-5p, -27b, -378, -26b, -23a, -23b were upregulated and hsa-miR-155, -20b, -221, -151-3p, -222, -29b/c, -106a were downregulated more than 2-fold due to EBV-infection of DLBCL. All known EBV miRNAs with the exception of the BHRF1 cluster as well as EBV-miR-BART15 and -20 were present. A computational analysis indicated potential targets such as c-MYB, LATS2, c-SKI and SIAH1. We show that c-MYB is targeted by miR-155 and miR-424, that the tumor suppressor SIAH1 is targeted by miR-424, and that c-SKI is potentially regulated by miR-155. Downregulation of SIAH1 protein in DLBCL was demonstrated by immunohistochemistry. The inhibition of SIAH1 is in line with the notion that EBV impedes various pro-apoptotic pathways during tumorigenesis. The down-modulation of the oncogenic c-MYB protein, although counter-intuitive, might be explained by its tight regulation in developmental processes.

Cathepsins B and L in peripheral blood mononuclear cells of pediatric acute myeloid leukemia: potential poor prognostic markers

The diagnostic and prognostic significance of cathepsin B (CTSB) and L (CTSL) is well documented for solid tumors. However, their significance in acute leukemias is lacking. This study was planned to investigate expression and significance of these proteases in peripheral blood mononuclear cells (PBMCs) of patients with pediatric acute myeloid leukemia (AML). CTSL and CTSB activities were assayed in PBMCs of 24 children with AML and ten healthy controls by spectrofluorimetry. The mRNA levels of these proteases and their specific endogenous inhibitor cystatin C and transcriptional upregulator vascular endothelial growth factor (VEGF) were quantitated by real-time PCR. Correlation analysis of CTSL and CTSB activities/expression with their inhibitor/upregulator and event-free survival (EFS) was done using appropriate statistical tools. CTSL and CTSB protease activity and their mRNA expression were significantly higher in AML patients compared to controls (p ≤ 0.001). A strong positive correlation was observed between VEGF expression and CTSL (r = 0.812; p ≤ 0.001). Similarly, VEGF exhibited a strong positive correlation with CTSB (r = 0.501; p = 0.013). Cystatin expression though significantly high (p ≤ 0.001) in AML was negatively correlated with CTSL (r = -0.920; p ≤ 0.001) and CTSB (r = -0.580, p ≤ 0.001) expression. AML patients with higher CTSL and CTSB activity exhibited an inferior EFS (CTSL: p = 0.045; CTSB: p = 0.002) and overall survival (OS; CTSL: p = 0.05; CTSB: p = 0.004) compared to patients with lower levels of these proteases. This is the first report demonstrating increased expression of CTSL and CTSB in AML, mechanism of their increased expression in relation to VEGF, and their association with poor EFS and OS. These results suggest a potential utility of these proteases as prognostic markers for this malignancy.

Poly(A) cDNA real-time PCR for indicator gene measurement in cancer

Microarray gene expression profiling has identified gene signatures or "Indicator" genes predictive of outcome in many cancer types including lymphoma, and more recently pancreatic cancer. This has identified novel and powerful diagnostic and prognostic and generically applicable markers, promising more specific diagnosis and treatment, together with improved understanding of pathobiology. There is now an urgent need to translate these signatures to clinical use. However, gene microarrays rely on relatively large amounts of fresh starting tissue obviating measurement of Indicator genes in routine practice, and there is a need for development of another, simple, robust, relatively inexpensive and sensitive method for their translation to clinical use. We have piloted the use of real-time PCR measurement of specific prognostic genes, so called "Indicator" genes, in globally amplified polyA cDNA for this purpose. Poly(A) PCR coordinately amplifies cDNA copies of all polyadenylated mRNAs, thereby generating a PCR product (polyA cDNA) whose composition reflects the relative abundance of all expressed genes in the starting sample. Poly(A) PCR enables global mRNA amplification from picogram amounts of RNA and has been routinely used to analyse expression in small samples including single cells. The poly(A) cDNA pool generated is also indefinitely renewable and as such represents a "molecular block". Real-time PCR measurement, using gene-specific primers and probes, of the expression levels of specific Indicator genes then allows gene signatures to be detected within the poly(A) cDNA, thereby enabling expression profiling of very small amounts of starting material. This chapter details this method as applied to fresh and paraffin embedded tissue and to pancreatic juice. In this chapter, we have concentrated on application of the method to pancreatic cancer, but the generic nature of the method renders it applicable to any cancer type, thereby representing a novel platform for cancer diagnosis across all tumour types.

Comparative expression of a set of genes to an internal housekeeping control in CDNA amplified and not amplified by PolyAPCR in non-Hodgkin's lymphoma samples obtained from fine-needle aspiration cytology

AIM

We aimed to evaluate the amount and quality of the RNA obtained from lymph nodes of non-Hodgkin lymphomas (NHLs) patients using fine-needle aspiration cytology (FNAC), and to develop strategies to overcome eventual technical drawbacks.

MATERIALS AND METHODS

Twenty-six patients with NHL and 10 tonsils from children submitted to tonsillectomy underwent FNAC. The aspirates were performed using both cytoaspirator (sample A) and syringe and needle (sample B). The RNA was extracted using Trizol reagent and transcribed with the Superscript kit (Invitrogen). The quality of RNA was verified through the amplification of a beta-actin 155-bp fragment.

RESULTS

Fifty-two NHL and 20 tonsil samples were analyzed. The total amount of RNA in the tonsil samples varied from <1.0 to 6.2 microg with cytoaspirator (A) and from <1.0 to 4.7 microg with syringe and needle (B). The total amount of RNA obtained from NHL varied from <1.0 to 6.5 microg with cytoaspirator (A) and <1.0 to 5.5 microg with syringe and needle. In an attempt to increase the amounts of RNA in each sample, we standardized the polyAPCR technique, which increased by 10 times the amount of cDNA in most of the test and control samples. The efficiency of the reaction was verified through the amplification of beta-actin, in which 100% of the test and control samples were amplified. When polyAPCR cDNA and nonamplified cDNA samples were paired to be evaluated by real-time PCR, using glyceraldehyde-3-phosphate dehydrogenase as the constitutive gene and nuclear factor-kappa B and NFkappaBIA as target genes, there was equivalence in the amplifications of 100% of the 15 evaluated samples.

CONCLUSIONS

Our results showed that FNAC, obtained either by cytoaspirator or syringe and needle, is a good source of small amounts of RNA. The polyAPCR technique significantly increased the amount of genomic material, which might be a cDNA source for future gene expression studies.

Poly(adenylic acid) complementary DNA real-time polymerase chain reaction in pancreatic ductal juice in patients undergoing pancreaticoduodenectomy

OBJECTIVES

There is a need to develop methods of early diagnosis for pancreatic cancer. Pancreatic juice is easily collected by endoscopic retrograde cholangiopancreatography and may facilitate diagnosis using molecular markers. The aim of this work was to explore the feasibility of measurement of gene expression in RNA isolated from ductal juice.

METHODS

Intraoperative sampling of pancreatic juice was undertaken in 27 patients undergoing pancreaticoduodenectomy for suspected tumor. Total RNA was extracted and used as template for poly(adenylic acid) (poly[A]) polymerase chain reaction (PCR) to generate a globally amplified complementary DNA pool representative of all expressed messenger RNAs. Real-time PCR was performed for trefoil factor 2 (TFF2), carboxypeptidase B1 (CPB1), and kallikrein-related peptidase 3 (KLK3) in a subset of samples; all samples were normalized for 3 reference genes (glyceraldehyde-3-phosphate dehydrogenase [GAPDH], PSMB6, and beta-2-microglobulin [B2M]).

RESULTS

The median volume of the pancreatic juice obtained was 1245 microL (range, 50-5000 microL). The RNA integrity number ranged from 1.9 to 10. Reverse transcriptase PCR was positive for pancreas-specific genes (TFF2 and CPB1) and negative for prostatic-specific antigen in all samples.

CONCLUSIONS

These results demonstrate that RNA analysis of pancreatic juice is feasible using a combination of poly(A) PCR and real-time PCR. In addition, the poly(A) complementary DNA generated can be probed for multiple genes and is indefinitely renewable, thereby representing a molecular block of importance for future research.

Acute myelogenous leukemia cells with the MLL-ELL translocation convert morphologically and functionally into adherent myofibroblasts

Bone marrow-myofibroblasts, a major component of bone marrow-stroma, are reported to originate from hematopoietic stem cells. We show in this paper that non-adherent leukemia blasts can change into myofibroblasts. When myeloblasts from two cases of acute myelogenous leukemia with a fusion product comprising mixed lineage leukemia and RNA polymerase II elongation factor, were cultured long term, their morphology changed to that of myofibroblasts with similar molecular characteristics to the parental myeloblasts. The original leukemia blasts, when cultured on the leukemia blast-derived myofibroblasts, grew extensively. Leukemia blasts can create their own microenvironment for proliferation.

Opposite expression pattern of Src kinase Lyn in acute and chronic haematological malignancies

Lck/yes-related novel (Lyn) tyrosine kinase overexpression has been suggested to be important for leukaemic cell growth making it an attractive target for therapy. By contrast, Lyn deficiency was shown to be responsible for a phenotype resembling myeloproliferative neoplasm (MPN) in mice. We aimed to shed more light on Lyn's role in haematological neoplasm and systematically investigated Lyn expression in MPN, acute and chronic leukaemia subtypes (n = 236). On top, B-cell chronic lymphocytic leukaemia (B-CLL) and chronic myeloid leukaemia significantly overexpressed Lyn when compared to de novo acute lymphoblastic leukaemia, de novo acute myeloid leukaemia (AML) and Philadelphia-chromosome-negative myeloproliferative neoplasms (p < 0.001). Most of acute leukaemia subtypes showed a notable down-regulation of Lyn mRNA but anyhow individual cases were labelled for the active form of Lyn protein. Intriguingly, secondary AML evolved in myelodysplastic syndromes revealed almost undetectable Lyn. Overexpression of Lyn in B-CLL was associated with a significant down-regulation of microRNA-337-5p suggesting that aberrant expression of this particular microRNA could be involved in post-transcriptional control of Lyn mRNA fate. We conclude that tyrosine kinase Lyn contributes to the malignant phenotype in certain leukaemia subtypes and therefore attracts targeted therapy.

Clinical quantitation of immune signature in follicular lymphoma by RT-PCR-based gene expression profiling

Microarray gene expression profiling studies have demonstrated immune response gene signatures that appear predictive of outcome in follicular lymphoma (FL). However, measurement of these marker genes in routine practice remains difficult. We have therefore investigated the immune response in FL using real-time polymerase chain reaction (PCR) to measure expression levels of 35 candidate Indicator genes, selected from microarray studies, to polyA cDNAs prepared from 60 archived human frozen lymph nodes, in parallel with immunohistochemical analysis for CD3, CD4, CD7, CD8, CD10, CD20, CD21, and CD68. High levels of CCR1, a marker of monocyte activation, were associated with a shorter survival interval, and high levels of CD3 with better survival, while immunohistochemistry demonstrated association of high numbers of CD68(+) macrophages with a shorter survival interval and of high numbers of CD7(+) T cells with a longer survival interval. The results confirm the role of the host immune response in outcome in FL and identify CCR1 as a prognostic indicator and marker of an immune switch between macrophages and a T cell-dominant response. They demonstrate the utility of polyA DNA and real-time PCR for measurement of gene signatures and the applicability of using this type of "molecular block" in clinical practice.

Global gene expression profiling reveals similarities and differences among mouse pluripotent stem cells of different origins and strains

Pluripotent stem cell lines with similar phenotypes can be derived from both blastocysts (embryonic stem cells, ESC) and primordial germ cells (embryonic germ cells, EGC). Here, we present a compendium DNA microarray analysis of multiple mouse ESCs and EGCs from different genetic backgrounds (strains 129 and C57BL/6) cultured under standard conditions and in differentiation-promoting conditions by the withdrawal of Leukemia Inhibitory Factor (LIF) or treatment with retinoic acid (RA). All pluripotent cell lines showed similar gene expression patterns, which separated them clearly from other tissue stem cells with lower developmental potency. Differences between pluripotent lines derived from different sources (ESC vs. EGC) were smaller than differences between lines derived from different mouse strains (129 vs. C57BL/6). Even in the differentiation-promoting conditions, these pluripotent cells showed the same general trends of gene expression changes regardless of their origin and genetic background. These data indicate that ESCs and EGCs are indistinguishable based on global gene expression patterns alone. On the other hand, a detailed comparison between a group of ESC lines and a group of EGC lines identified 20 signature genes whose average expression levels were consistently higher in ESC lines, and 84 signature genes whose average expression levels were consistently higher in EGC lines, irrespective of mouse strains. Similar analysis identified 250 signature genes whose average expression levels were consistently higher in a group of 129 cell lines, and 337 signature genes whose average expression levels were consistently higher in a group of C57BL/6 cell lines. Although none of the genes was exclusively expressed in either ESCs versus EGCs or 129 versus C57BL/6, in combination these signature genes provide a reliable separation and identification of each cell type. Differentiation-promoting conditions also revealed some minor differences between the cell lines. For example, in the presence of RA, EGCs showed a lower expression of muscle- and cardiac-related genes and a higher expression of gonad-related genes than ESCs. Taken together, the results provide a rich source of information about the similarities and differences between ESCs and EGCs as well as 129 lines and C57BL/6 lines. Such information will be crucial to our understanding of pluripotent stem cells. The results also underscore the importance of studying multiple cell lines from different strains when making comparisons based on gene expression analysis.

Clinical quantitation of diagnostic and predictive gene expression levels in follicular and diffuse large B-cell lymphoma by RT-PCR gene expression profiling

Recent microarray gene expression profiling studies have identified gene signatures predictive of outcome, so-called "indicator" genes, for diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). However, measurement of these genes in routine practice remains difficult. We applied real-time polymerase chain reaction (PCR) to polyA cDNAs prepared from 106 archived human frozen lymph nodes (63 of FL, 25 of DLBCL, 10 reactive lymph nodes, and cases with paired samples of FL [4] and subsequent DLBCL [4]). Reverse transcription and polyA reverse transcriptase (RT)-PCR was performed, and resultant cDNA was probed by real-time PCR for 36 candidate indicator genes, selected from microarray studies. Nine genes showed statistically significant different expression between FL and DLBCL, including cyclin B, COL3A1, NPM3, H731, PRKCB1, OVGL, ZFPC150, HLA-DQ-a, and XPB. Of these, cyclin B, NPM3, and COL3A1 were higher in DLBCL. Six genes showed statistically significant higher expression in the neoplastic nodes compared with reactive nodes, namely PRKCB1, BCL-6, EAR2, ZFX, cyclin B, YY1. High levels of YY.1 were associated with a shorter survival interval in both FL and DLBCL. The method is simple, sensitive, and robust, facilitating routine use and may be used as a platform for clinical measurement of prognostic gene signatures.

Gene expression analysis of myeloid and lymphoid lineage markers during mouse haematopoiesis

Expression profiling of haematopoietic cells is hampered by the heterogeneous nature of haematopoietic tissues and the absolute rarity of early unrestricted progenitors. To overcome this, the expression profile of lymphoid and myeloid-associated genes (LEF1, EBF, CD19, Sox-4, B29, CD45, C-fms, lysozyme, PU.1 and CD5) were investigated in 40 mouse myeloid haematopoietic precursors covering the entire haematopoietic hierarchy from multipotential to committed single lineages. The lineage-specific expression seen in single-cell studies was confirmed by examining fractionated bone marrow, whole tissues and differentiation of the multipotent cell line FDCP (Factor Dependent Cell Paterson) mix. Analysis of the 40 single myeloid precursors failed to detect expression of lymphoid-associated genes, LEF1, EBF, CD19 and CD5, despite detection in lymphoid cell controls. Surprisingly, the lymphoid-associated genes, Sox-4 and B29 were detected in the single myeloid precursors, which was confirmed in bone marrow and a multipotential myeloid cell line. The pattern of Sox-4 and B29, is consistent with a potential role in the commitment of bipotential granulocytic/macrophage precursors towards the granulocyte or macrophage lineage. In addition to providing baseline values for myeloid and lymphoid lineage markers during mouse haematopoiesis, these results highlight the importance of single-cell analysis in the study of complex tissues.

Comparison of gene-expression profiles in parallel bone marrow and peripheral blood samples in acute myeloid leukaemia by real-time polymerase chain reaction

BACKGROUND

Gene signatures (Indicator genes) in bone marrow that provide more precise prognostication in haematological malignancy have been identified by microarray expression studies. It would be beneficial to measure these diagnostic signatures in peripheral blood.

AIMS

To determine the degree of correspondence of gene expression for a set of Indicator genes between bone marrow and peripheral blood in acute myeloid leukaemia (AML).

METHODS

Parallel bone marrow aspirate and peripheral blood samples were obtained from 19 patients diagnosed with AML and mononuclear cells isolated from both sample types. mRNA was globally amplified by polyadenylated real-time polymerase chain reaction (polyA RT-PCR); the expression of 15 AML Indicator genes, identified from previous microarray studies, was measured by RT-PCR. All values were normalised to the mean expression of three housekeeping genes (IF2-beta, GAP and RbS9) and were statistically compared using SPSS software.

RESULTS

No significant difference in expression between bone marrow and peripheral blood was observed for 10 of the genes (leptin receptor, CD33, adipsin, proteoglycan 1, MB-1, cyclin D3, hSNF2b, proteasome iota, HkrT-1 and E2A), indicating its possible use in monitoring disease activity in peripheral blood samples, whereas c-myb, HOXA9, LYN, cystatin c and LTC4s showed significantly different expression between bone marrow and peripheral blood samples.

CONCLUSION

These results indicate a possible use for the method in monitoring AML in peripheral blood by RT-PCR measurement of Indicator genes. In addition, the initial use of polyA PCR facilitates translation to very small clinical samples, including fractionated cell populations, of particular importance for monitoring haematological malignancy.

Correlation analysis of two-dimensional gel electrophoretic protein patterns and biological variables

BACKGROUND

Two-dimensional gel electrophoresis (2DE) is a powerful technique to examine post-translational modifications of complexly modulated proteins. Currently, spot detection is a necessary step to assess relations between spots and biological variables. This often proves time consuming and difficult when working with non-perfect gels. We developed an analysis technique to measure correlation between 2DE images and biological variables on a pixel by pixel basis. After image alignment and normalization, the biological parameters and pixel values are replaced by their specific rank. These rank adjusted images and parameters are then put into a standard linear Pearson correlation and further tested for significance and variance.

RESULTS

We validated this technique on a set of simulated 2DE images, which revealed also correct working under the presence of normalization factors. This was followed by an analysis of p53 2DE immunoblots from cancer cells, known to have unique signaling networks. Since p53 is altered through these signaling networks, we expected to find correlations between the cancer type (acute lymphoblastic leukemia and acute myeloid leukemia) and the p53 profiles. A second correlation analysis revealed a more complex relation between the differentiation stage in acute myeloid leukemia and p53 protein isoforms.

CONCLUSION

The presented analysis method measures relations between 2DE images and external variables without requiring spot detection, thereby enabling the exploration of biosignatures of complex signaling networks in biological systems.