Deletion of Grin1 in mouse megakaryocytes reveals NMDA receptor role in platelet function and proplatelet formation.

The process of proplatelet formation (PPF) requires coordinated interaction between megakaryocytes (MKs) and the extracellular matrix (ECM), followed by a dynamic reorganization of the actin and microtubule cytoskeleton. Localized fluxes of intracellular calcium ions (Ca2+) facilitate MK-ECM interaction and PPF. Glutamate-gated N-methyl-D-aspartate receptor (NMDAR) is highly permeable to Ca2+. NMDAR antagonists inhibit MK maturation ex vivo; however, there are no in vivo data. Using the Cre-loxP system, we generated a platelet lineage-specific knockout mouse model of reduced NMDAR function in MKs and platelets (Pf4-Grin1-/- mice). Effects of NMDAR deletion were examined using well-established assays of platelet function and production in vivo and ex vivo. We found that Pf4-Grin1-/- mice had defects in megakaryopoiesis, thrombopoiesis, and platelet function, which manifested as reduced platelet counts, lower rates of platelet production in the immune model of thrombocytopenia, and prolonged tail bleeding time. Platelet activation was impaired to a range of agonists associated with reduced Ca2+ responses, including metabotropic like, and defective platelet spreading. MKs showed reduced colony and proplatelet formation. Impaired reorganization of intracellular F-actin and α-tubulin was identified as the main cause of reduced platelet function and production. Pf4-Grin1-/- MKs also had lower levels of transcripts encoding crucial ECM elements and enzymes, suggesting NMDAR signaling is involved in ECM remodeling. In summary, we provide the first genetic evidence that NMDAR plays an active role in platelet function and production. NMDAR regulates PPF through a mechanism that involves MK-ECM interaction and cytoskeletal reorganization. Our results suggest that NMDAR helps guide PPF in vivo.

Identification of novel biomarkers for the prediction of subclinical coronary artery atherosclerosis in patients with rheumatoid arthritis: an exploratory analysis.

BACKGROUND: Cardiovascular (CV) risk estimation calculators for the general population underperform in patients with rheumatoid arthritis (RA). The purpose of this study was to identify relevant protein biomarkers that could be added to traditional CV risk calculators to improve the capacity of coronary artery calcification (CAC) prediction in individuals with RA. In a second step, we quantify the improvement of this prediction of CAC when these circulating biomarkers are added to standard risk scores. METHODS: A panel of 141 serum and plasma proteins, which represent a broad base of both CV and RA biology, were evaluated and prioritized as candidate biomarkers. Of these, 39 proteins were selected and measured by commercial ELISA or quantitative mass spectroscopy in 561 individuals with RA in whom a measure of CAC and frozen sera were available. The patients were randomly split 50:50 into a training/validation cohort. Discrimination (using area under the receiver operator characteristic curves) and re-classification (through net reclassification improvement and integrated discrimination improvement calculation) analyses were performed first in the training cohort and replicated in the validation cohort, to estimate the increase in prediction accuracy for CAC using the ACA/AHA (American College of Cardiology and the American Heart Association) score with, compared to without, addition of these circulating biomarkers. RESULTS: The model containing ACC/AHA score plus cytokines (osteopontin, cartilage glycoprotein-39, cystatin C, and chemokine (C-C motif) ligand 18) and plus quantitative mass spectroscopy biomarkers (serpin D1, paraoxonase, and clusterin) had a statistically significant positive net reclassifications index and integrated discrimination improvement for the prediction of CAC, using ACC/AHA score without any biomarkers as the reference category. These results were confirmed in the validation cohort. CONCLUSION: In this exploratory analysis, the addition of several circulating CV and RA biomarkers to a standard CV risk calculator yielded significant improvements in discrimination and reclassification for the presence of CAC in individuals with RA.

Estrogen receptor signaling promotes dendritic cell differentiation by increasing expression of the transcription factor IRF4.

During inflammation, elevated granulocyte macrophage-colony-stimulating factor (GM-CSF) directs the development of new dendritic cells (DCs). This pathway is influenced by environmental factors, and we previously showed that physiologic levels of estradiol, acting through estrogen receptor alpha (ERalpha), promote the GM-CSF-mediated differentiation of a CD11b(+) DC subset from myeloid progenitors (MPs). We now have identified interferon regulatory factor 4 (IRF4), a transcription factor induced by GM-CSF and critical for CD11b(+) DC development in vivo, as a target of ERalpha signaling during this process. In MPs, ERalpha potentiates and sustains GM-CSF induction of IRF4. Furthermore, retroviral delivery of the Irf4 cDNA to undifferentiated ERalpha(-/-) bone marrow cells restored the development of the estradiol/ERalpha-dependent DC population, indicating that an elevated amount of IRF4 protein substitutes for ERalpha signaling. Thus at an early stage in the MP response to GM-CSF, ERalpha signaling induces an elevated amount of IRF4, which leads to a developmental program underlying CD11b(+) DC differentiation.

Erroneous augmentation of multiplex assay measurements in patients with rheumatoid arthritis due to heterophilic binding by serum rheumatoid factor.

OBJECTIVE: Serum rheumatoid factor (RF) and other heterophilic antibodies potentially interfere with antibody-based immunoassays by nonspecifically binding detection reagents. The purpose of this study was to assess whether these factors confound multiplex-based immunoassays, which are used with increasing frequency to measure cytokine and chemokine analytes in patients with rheumatoid arthritis (RA). METHODS: We performed multiplex immunoassays using different platforms to measure analyte concentrations in RA patient samples. Samples were depleted of RF by column-based affinity absorption or were exposed to agents that block heterophilic binding activity. RESULTS: In RA patients with high-titer RF, 69% of analytes demonstrated at least a 2-fold stronger multiplex signal in non-RF-depleted samples as compared to RF-depleted samples. This degree of erroneous signal amplification was less frequent in low-titer RF samples (17% of analytes; P < 0.0000001). Signal amplification by heterophilic antibodies was blocked effectively by HeteroBlock (≥ 150 µg/ml). In 35 RA patients, multiplex signals for 14 of 22 analytes were amplified erroneously in unblocked samples as compared to blocked samples (some >100-fold), but only in patients with high-titer RF (P < 0.002). Two other blocking agents, heterophilic blocking reagent and immunoglobulin-inhibiting reagent, also blocked heterophilic activity. CONCLUSION: All multiplex protein detection platforms we tested exhibited significant confounding by RF or other heterophilic antibodies. These findings have broad-reaching implications in the acquisition and interpretation of data derived from multiplex immunoassay testing of RA patient serum and possibly also in other conditions in which RF or other heterophilic antibodies may be present. Several available blocking agents effectively suppressed this erroneous signal amplification in the multiplex platforms tested.

Clinically Relevant Biology of Hyaluronic Acid in the Desmoplastic Stroma of Pancreatic Ductal Adenocarcinoma.

ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is notorious for its poor outcome. The presence of a dense desmoplastic stroma is a hallmark of this malignancy, and abundant hyaluronic acid (HA) within this stroma is a common feature of PDAC. At the end of 2019, an HA-targeting drug, after initial promise, failed phase 3 clinical trials in PDAC. This failure in the face of such strong evidence for biological importance forces us to turn back to the research and seek a better understanding of HA biology in PDAC. Therefore, in this review, we reexamine what is known about HA biology, the methods used to detect and quantify HA, and the ability of the biological models in which HA has been investigated to recapitulate an HA-rich desmoplastic tumor stroma. The role of HA in PDAC relies on its complex interplay with a range of HA-associated molecules, which have not been as extensively investigated as HA itself. Therefore, using large genomic data sets, we cataloged the abundance and activity in PDAC of molecules that modulate HA synthesis, degradation, protein interactions, and receptor binding. Based on their association with clinical characteristics and individual patient outcomes, we suggest a small number of HA-associated molecules that warrant further investigation as biomarkers and drug targets.

Breast Cancer Patient Prognosis Is Determined by the Interplay between TP53 Mutation and Alternative Transcript Expression: Insights from TP53 Long Amplicon Digital PCR Assays.

The TP53 gene locus is capable of producing multiple RNA transcripts encoding the different p53 protein isoforms. We recently described multiplex long amplicon droplet digital PCR (ddPCR) assays to quantify seven of eight TP53 reference transcripts in human tumors. Here, we describe a new long amplicon ddPCR assay to quantify expression of the eighth TP53 reference transcript encoding ∆40p53α. We then applied these assays, alongside DNA sequencing of the TP53 gene locus, to tumors from a cohort of New Zealand (NZ) breast cancer patients. We found a high prevalence of mutations at TP53 splice sites in the NZ breast cancer cohort. Mutations at TP53 intron 4 splice sites were associated with overexpression of ∆133TP53 transcripts. Cox proportional hazards survival analysis showed that interplay between TP53 mutation status and expression of TP53 transcript variants was significantly associated with patient outcome, over and above standard clinical and pathological information. In particular, patients with no TP53 mutation and a low ratio of TP53 transcripts t2 to t1, which derive from alternative intron 1 acceptor splice sites, had a remarkably good outcome. We suggest that this type of analysis, integrating mutation and transcript expression, provides a step-change in our understanding of TP53 in cancer.

Neuropilin-VEGF signaling pathway acts as a key modulator of vascular, lymphatic, and inflammatory cell responses of the bladder to intravesical BCG treatment.

Recent findings indicate that VEGF receptors and coreceptors (neuropilins; NRP) are expressed on nonendothelial cells in human bladder urothelium, in one human bladder cancer cell line (J82), and in the mouse bladder urothelium. In addition, VEGFR1, VEGFR2, NRP1, and NRP2 expressions were upregulated in animal models of chronic bladder inflammation induced by four weekly instillations of protease-activated receptors (PAR)-activating peptides or bacillus Calmette-Guérin (BCG) into the mouse bladder. Here, we used four weekly instillations of BCG as a model for chronic bladder inflammation to further investigate whether VEGF receptors and NRPs play a role in the migration of inflammatory cells and inflammation-induced lymphangiogenesis and angiogenesis. For this purpose, we used neutralizing antibodies that were engineered to specifically block the binding of VEGF to NRP (anti-NRP1(B)) and the binding of semaphorins to NRP (anti-NRP1(A)). C57BL/6 mice received intraperitoneal injections of PBS, anti-NRP1(A)- or anti-NRP1(B)-neutralizing antibodies and then were challenged chronically with intravesical PBS or BCG. At the end of chronic challenge period, a fluorescent internalizable tracer, scVEGF/Cy5.5, was administered to all mice and near-infrared fluorescence images were obtained in vivo and in real time. BCG increased the overall accumulation of scVEGF/Cy5.5 in the urinary bladder urothelium and inflammatory cells. In addition, BCG increased the density of blood and lymphatic vessels concomitantly with an upregulation of NRP2 expression in lymphatic vessels. Treatment of the mice with NRP1-neutralizing antibodies dramatically reduced scVEGF/Cy5.5 uptake, polymorphonuclear (myeloperoxidase-positive cells) and dendritic cell (CD11c-positive cells) infiltration, and decreased the overall density of BCG-induced blood and lymphatic vessels. These results implicate NRPs as critical in vivo regulators of the vascular and inflammatory responses to the intravesical administration of BCG.

Idiopathic inflammatory myopathies, signified by distinctive peripheral cytokines, chemokines and the TNF family members B-cell activating factor and a proliferation inducing ligand.

OBJECTIVE: Serum cytokines play an important role in the pathogenesis of myositis by initiating and perpetuating various cellular and humoral autoimmune processes. The aim of the present study was to describe a broad spectrum of T- and B-cell cytokines, growth factors and chemokines in patients with idiopathic inflammatory myopathies (IIMs) and healthy individuals. METHODS: A protein array system, denoted as multiplex cytokine assay was utilized to measure simultaneously the levels of 24 circulating cytokines, including B-cell activating factor (BAFF) and a proliferation inducing ligand (APRIL) of patients with IIMs and healthy individuals. Additionally, correlational clustering and discriminant function analysis (DFA), two multivariate, supervised analysis methods were employed to identify a subset of biomarkers in order to describe potential functional interrelationships among these pathological cytokines. RESULTS: Univariate analysis demonstrated that a complex set of immune and inflammatory modulating cytokines are significantly up-regulated in patients with IIMs relative to unaffected controls including IL-10, IL-13, IFN-α, epidermal growth factor (EGF), VEGF, fibroblast growth factor (FGF), CCL3 [macrophage inflammatory protein (MIP-1α)], CCL4 (MIP-1ß) and CCL11 (eotaxin), whereas G-CSF was significantly reduced in IIM patients. Correlational clustering was able to discriminate between, and hence sub-classify patients with IIMs. DFA identified EGF, IFN-α, VEGF, CCL3 (MIP-1α) and IL-12p40, as analytes with the strongest discriminatory power among various myositis patients and controls. CONCLUSIONS: Our findings suggest that these factors modulate myositis pathology and help to identify differences between subsets of the disease.

Accessing a New Dimension in TP53 Biology: Multiplex Long Amplicon Digital PCR to Specifically Detect and Quantitate Individual TP53 Transcripts.

TP53, the most commonly-mutated gene in cancer, undergoes complex alternative splicing. Different TP53 transcripts play different biological roles, both in normal function and in the progression of diseases such as cancer. The study of TP53's alternative RNA splice forms and their use as clinical biomarkers has been hampered by limited specificity and quantitative accuracy of current methods. TP53 RNA splice variants differ at both 5' and 3' ends, but because they have a common central region of 618 bp, the individual TP53 transcripts are impossible to specifically detect and precisely quantitate using standard PCR-based methods or short-read RNA sequencing. Therefore, we devised multiplex probe-based long amplicon droplet digital PCR (ddPCR) assays, which for the first time allow precise end-to-end quantitation of the seven major TP53 transcripts, with amplicons ranging from 0.85 to 1.85 kb. Multiple modifications to standard ddPCR assay procedures were required to enable specific co-amplification of these long transcripts and to overcome issues with secondary structure. Using these assays, we show that several TP53 transcripts are co-expressed in breast cancers, and illustrate the potential for this method to identify novel TP53 transcripts in tumour cells. This capability will facilitate a new level of biological and clinical understanding of the alternatively-spliced TP53 isoforms.

N-Methyl-D-Aspartate Receptor Hypofunction in Meg-01 Cells Reveals a Role for Intracellular Calcium Homeostasis in Balancing Megakaryocytic-Erythroid Differentiation.

The release of calcium ions (Ca2+) from the endoplasmic reticulum (ER) and related store-operated calcium entry (SOCE) regulate maturation of normal megakaryocytes. The N-methyl-D-aspartate (NMDA) receptor (NMDAR) provides an additional mechanism for Ca2+ influx in megakaryocytic cells, but its role remains unclear. We created a model of NMDAR hypofunction in Meg-01 cells using CRISPR-Cas9 mediated knockout of the GRIN1 gene, which encodes an obligate, GluN1 subunit of the NMDAR. We found that compared with unmodified Meg-01 cells, Meg-01-GRIN1 -/- cells underwent atypical differentiation biased toward erythropoiesis, associated with increased basal ER stress and cell death. Resting cytoplasmic Ca2+ levels were higher in Meg-01-GRIN1 -/- cells, but ER Ca2+ release and SOCE were lower after activation. Lysosome-related organelles accumulated including immature dense granules that may have contributed an alternative source of intracellular Ca2+. Microarray analysis revealed that Meg-01-GRIN1 -/- cells had deregulated expression of transcripts involved in Ca2+ metabolism, together with a shift in the pattern of hematopoietic transcription factors toward erythropoiesis. In keeping with the observed pro-cell death phenotype induced by GRIN1 deletion, memantine (NMDAR inhibitor) increased cytotoxic effects of cytarabine in unmodified Meg-01 cells. In conclusion, NMDARs comprise an integral component of the Ca2+ regulatory network in Meg-01 cells that help balance ER stress and megakaryocytic-erythroid differentiation. We also provide the first evidence that megakaryocytic NMDARs regulate biogenesis of lysosome-related organelles, including dense granules. Our results argue that intracellular Ca2+ homeostasis may be more important for normal megakaryocytic and erythroid differentiation than currently recognized; thus, modulation may offer therapeutic opportunities.

A Predictor of Early Disease Recurrence in Patients With Breast Cancer Using a Cell-free RNA and Protein Liquid Biopsy.

INTRODUCTION: Circulating biomarkers have been increasingly used in the clinical management of breast cancer. The present study evaluated whether RNAs and a protein present in the plasma of patients with breast cancer might have utility as prognostic biomarkers complementary to existing clinical tests. PATIENTS AND METHODS: We performed microarray profiling of small noncoding RNAs in plasma samples from 30 patients with breast cancer and 10 control individuals. Two small noncoding RNAs, including microRNA (miR)-923, were selected and quantified in plasma samples from an evaluation cohort of 253 patients with breast cancer, using droplet digital polymerase chain reaction. We also measured cancer antigen (CA) 15-3 protein levels in these samples. Cox regression survival analysis was used to determine which markers were associated with patient prognosis. RESULTS: As independent markers of prognosis, the plasma levels of miR-923 and CA 15-3 at the time of surgery for breast cancer were significantly associated with prognosis, irrespective of treatment (Cox proportional hazards, P = 3.9 × 10-3 and 1.9 × 10-9, respectively). After building a multivariable model with standard clinical and pathological features, the addition of miR-923 and CA 15-3 information into the model resulted in a significantly better predictor of disease recurrence in patients, irrespective of treatment, compared with the use of clinicopathological data alone (area under the curve at 3 years, 0.858 vs. 0.770 with clinicopathological markers only; P = .017). CONCLUSION: We propose that the plasma levels of miR-923 and CA 15-3, combined with standard clinicopathological predictors, could be used as a preoperative, noninvasive estimate of patient prognosis to identify which women might need more aggressive treatment or closer surveillance after surgery for breast cancer.

A new model of reproductive aging: the decline in ovarian non-growing follicle number from birth to menopause.

BACKGROUND: The primary determinant of reproductive age in women is the number of ovarian non-growing (primordial, intermediate and primary) follicles (NGFs). To better characterize the decline in NGF number associated with aging, we have employed modern stereology techniques to determine NGF number in women from birth to menopause. METHODS: Normal human ovaries were collected from 122 women (aged 0-51 years) undergoing elective oophorectomy, organ donation or autopsy. After gross pathologic examination, systematic random sampling was utilized to obtain tissue for analysis by the fractionator/optical disector method. Models to describe the resulting decay curve were constructed and evaluated. RESULTS: NGF decay was best described by a simple power function: log (y) = ax(b) + c, where a, b and c are constants and y = NGF count at age x (R(2) = 0.84, Sums of Squares Error = 28.18 on 119 degrees of freedom). This model implies that follicles decay faster with increasing age. CONCLUSIONS: Unlike previous models of ovarian follicle depletion, our model predicts no sudden change in decay rate, but rather a constantly increasing rate. The model not only agrees well with observed ages of menopause in women, but also is more biologically plausible than previous models. Although the model represents a significant improvement compared with earlier attempts, a considerable percentage of the variation in NGF number between women cannot be explained by age alone.

Recurrent loss of heterozygosity correlates with clinical outcome in pancreatic neuroendocrine cancer.

Pancreatic neuroendocrine tumors (pNETs) are uncommon cancers arising from pancreatic islet cells. Here we report the analysis of gene mutation, copy number, and RNA expression of 57 sporadic well-differentiated pNETs. pNET genomes are dominated by aneuploidy, leading to concordant changes in RNA expression at the level of whole chromosomes and chromosome segments. We observed two distinct patterns of somatic pNET aneuploidy that are associated with tumor pathology and patient prognosis. Approximately 26% of the patients in this series had pNETs with genomes characterized by recurrent loss of heterozygosity (LoH) of 10 specific chromosomes, accompanied by bi-allelic MEN1 inactivation and generally poor clinical outcome. Another ~40% of patients had pNETs that lacked this recurrent LoH pattern but had chromosome 11 LoH, bi-allelic MEN1 inactivation, and universally good clinical outcome. The somatic aneuploidy allowed pathogenic germline variants (e.g., ATM) to be expressed unopposed, with RNA expression patterns showing inactivation of downstream tumor suppressor pathways. No prognostic associations were found with tumor morphology, single gene mutation, or expression of RNAs reflecting the activity of immune, differentiation, proliferative or tumor suppressor pathways. In pNETs, single gene mutations appear to be less important than aneuploidy, with MEN1 the only statistically significant recurrently mutated driver gene. In addition, only one pNET in the series had clearly actionable single nucleotide variants (SNVs) (in PTEN and FLCN) confirmed by corroborating RNA expression changes. The two clinically relevant patterns of LoH described here define a novel oncogenic mechanism and a plausible route to genomic precision oncology for this tumor type.

Evofosfamide for the treatment of human papillomavirus-negative head and neck squamous cell carcinoma.

Evofosfamide (TH-302) is a clinical-stage hypoxia-activated prodrug of a DNA-crosslinking nitrogen mustard that has potential utility for human papillomavirus (HPV) negative head and neck squamous cell carcinoma (HNSCC), in which tumor hypoxia limits treatment outcome. We report the preclinical efficacy, target engagement, preliminary predictive biomarkers and initial clinical activity of evofosfamide for HPV-negative HNSCC. Evofosfamide was assessed in 22 genomically characterized cell lines and 7 cell line-derived xenograft (CDX), patient-derived xenograft (PDX), orthotopic, and syngeneic tumor models. Biomarker analysis used RNA sequencing, whole-exome sequencing, and whole-genome CRISPR knockout screens. Five advanced/metastatic HNSCC patients received evofosfamide monotherapy (480 mg/m2 qw × 3 each month) in a phase 2 study. Evofosfamide was potent and highly selective for hypoxic HNSCC cells. Proliferative rate was a predominant evofosfamide sensitivity determinant and a proliferation metagene correlated with activity in CDX models. Evofosfamide showed efficacy as monotherapy and with radiotherapy in PDX models, augmented CTLA-4 blockade in syngeneic tumors, and reduced hypoxia in nodes disseminated from an orthotopic model. Of 5 advanced HNSCC patients treated with evofosfamide, 2 showed partial responses while 3 had stable disease. In conclusion, evofosfamide shows promising efficacy in aggressive HPV-negative HNSCC, with predictive biomarkers in development to support further clinical evaluation in this indication.

Discriminators of mouse bladder response to intravesical Bacillus Calmette-Guerin (BCG).

BACKGROUND: Intravesical Bacillus Calmette-Guerin (BCG) is an effective treatment for bladder superficial carcinoma and it is being tested in interstitial cystitis patients, but its precise mechanism of action remains poorly understood. It is not clear whether BCG induces the release of a unique set of cytokines apart from its pro-inflammatory effects. Therefore, we quantified bladder inflammatory responses and alterations in urinary cytokine protein induced by intravesical BCG and compared the results to non-specific pro-inflammatory stimuli (LPS and TNF-alpha). We went further to determine whether BCG treatment alters cytokine gene expression in the urinary bladder. METHODS: C57BL/6 female mice received four weekly instillations of BCG, LPS, or TNF-alpha. Morphometric analyses were conducted in bladders isolated from all groups and urine was collected for multiplex analysis of 18 cytokines. In addition, chromatin immune precipitation combined with real-time polymerase chain reaction assay (CHIP/Q-PCR) was used to test whether intravesical BCG would alter bladder cytokine gene expression. RESULTS: Acute BCG instillation induced edema which was progressively replaced by an inflammatory infiltrate, composed primarily of neutrophils, in response to weekly administrations. Our morphological analysis suggests that these polymorphonuclear neutrophils are of prime importance for the bladder responses to BCG. Overall, the inflammation induced by BCG was higher than LPS or TNF-alpha treatment but the major difference observed was the unique granuloma formation in response to BCG. Among the cytokines measured, this study highlighted the importance of IL-1beta, IL-2, IL-3, IL-4, IL-6, IL-10, IL-17, GM-CSF, KC, and Rantes as discriminators between generalized inflammation and BCG-specific inflammatory responses. CHIP/Q-PCR indicates that acute BCG instillation induced an up-regulation of IL-17A, IL-17B, and IL-17RA, whereas chronic BCG induced IL-17B, IL-17RA, and IL-17RB. CONCLUSION: To the best of our knowledge, the present work is the first to report that BCG induces an increase in the IL-17 family genes. In addition, BCG induces a unique type of persisting bladder inflammation different from TNF-alpha, LPS, and, most likely, other classical pro-inflammatory stimuli.

Gene expression profiling of breast tumours from New Zealand patients.

AIMS: New Zealand has one of the highest rates of breast cancer incidence in the world. We investigated the gene expression profiles of breast tumours from New Zealand patients, compared them to gene expression profiles of international breast cancer cohorts and identified any associations between altered gene expression and the clinicopathological features of the tumours. METHODS: Affymetrix microarrays were used to measure the gene expression profiles of 106 breast tumours from New Zealand patients. Gene expression data from six international breast cancer cohorts were collated, and all the gene expression data were analysed using standard bioinformatic and statistical tools. RESULTS: Gene expression profiles associated with tumour ER and ERBB2 status, molecular subtype and selected gene expression signatures within the New Zealand cohort were consistent with those found in international cohorts. Significant differences in clinicopathological features such as tumour grade, tumour size and lymph node status were also observed between the New Zealand and international cohorts. CONCLUSIONS: Gene expression profiles, which are a sensitive indicator of tumour biology, showed no clear difference between breast tumours from New Zealand patients and those from non-New Zealand patients. This suggests that other factors may contribute to the high and increasing breast cancer incidence in New Zealand compared to international populations.

Analysis of the interaction of extracellular matrix and phenotype of bladder cancer cells.

BACKGROUND: The extracellular matrix has a major effect upon the malignant properties of bladder cancer cells both in vitro in 3-dimensional culture and in vivo. Comparing gene expression of several bladder cancer cells lines grown under permissive and suppressive conditions in 3-dimensional growth on cancer-derived and normal-derived basement membrane gels respectively and on plastic in conventional tissue culture provides a model system for investigating the interaction of malignancy and extracellular matrix. Understanding how the extracellular matrix affects the phenotype of bladder cancer cells may provide important clues to identify new markers or targets for therapy. METHODS: Five bladder cancer cell lines and one immortalized, but non-tumorigenic, urothelial line were grown on Matrigel, a cancer-derived ECM, on SISgel, a normal-derived ECM, and on plastic, where the only ECM is derived from the cells themselves. The transcriptomes were analyzed on an array of 1186 well-annotated cancer derived cDNAs containing most of the major pathways for malignancy. Hypervariable genes expressing more variability across cell lines than a set expressing technical variability were analyzed further. Expression values were clustered, and to identify genes most likely to represent biological factors, statistically over-represented ontologies and transcriptional regulatory elements were identified. RESULTS: Approximately 400 of the 1186 total genes were expressed 2 SD above background. Approximately 100 genes were hypervariable in cells grown on each ECM, but the pattern was different in each case. A core of 20 were identified as hypervariable under all 3 growth conditions, and 33 were hypervariable on both SISgel and Matrigel, but not on plastic. Clustering of the hypervariable genes showed very different patterns for the same 6 cell types on the different ECM. Even when loss of cell cycle regulation was identified, different genes were involved, depending on the ECM. Under the most permissive conditions of growth where the malignant phenotype was fully expressed, activation of AKT was noted. TGFbeta1 signaling played a major role in the response of bladder cancer cells to ECM. Identification of TREs on genes that clustered together suggested some clustering was driven by specific transcription factors. CONCLUSION: The extracellular matrix on which cancer cells are grown has a major effect on gene expression. A core of 20 malignancy-related genes were not affected by matrix, and 33 were differentially expressed on 3-dimensional culture as opposed to plastic. Other than these genes, the patterns of expression were very different in cells grown on SISgel than on Matrigel or even plastic, supporting the hypothesis that growth of bladder cancer cells on normal matrix suppresses some malignant functions. Unique underlying regulatory networks were driving gene expression and could be identified by the approach outlined here.

Hypervariable genes--experimental error or hidden dynamics.

In a homogeneous group of samples, not all genes of high variability stem from experimental errors in microarray experiments. These expression variations can be attributed to many factors including natural biological oscillations or metabolic processes. The behavior of these genes can tease out important clues about naturally occurring dynamic processes in the organism or experimental system under study. We developed a statistical procedure for the selection of genes with high variability denoted hypervariable (HV) genes. After the exclusion of low expressed genes and a stabilizing log-transformation, the majority of genes have comparable residual variability. Based on an F-test, HV genes are selected as having a statistically significant difference from the majority of variability stabilized genes measured by the 'reference group'. A novel F-test clustering technique, further noted as 'F-means clustering', groups HV genes with similar variability patterns, presumably from their participation in a common dynamic biological process. F-means clustering establishes, for the first time, groups of co-expressed HV genes and is illustrated with microarray data from patients with juvenile rheumatoid arthritis and healthy controls.

Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays.

BACKGROUND: Several aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normalization methods rely on the premise that most genes in compared samples are expressed at similar levels and therefore require accurate identification of nonexpressed genes (additive noise) so that they can be excluded from the normalization procedure. Moreover, key regulatory genes can maintain stringent control of a given response at low expression levels. If arbitrary cutoffs are used for distinguishing expressed from nonexpressed genes, some of these key regulatory genes may be unnecessarily excluded from the analysis. Unfortunately, no accurate method for differentiating additive noise from genes expressed at low levels is currently available. RESULTS: We developed a multistep procedure for analysis of mRNA expression data that robustly identifies the additive noise in a microarray experiment. This analysis is predicated on the fact that additive noise signals can be accurately identified by both distribution and statistical analysis. CONCLUSIONS: Identification of additive noise in this manner allows exclusion of noncorrelated weak signals from regression-based normalization of compared profiles thus maximizing the accuracy of these methods. Moreover, genes expressed at very low levels can be clearly identified due to the fact that their expression distribution is stable and distinguishable from the random pattern of additive noise.