A novel, efficient sampling method for biomolecules is proposed. The partial multicanonical molecular dynamics (McMD) was recently developed as a method that improved generalized ensemble (GE) methods to focus sampling only on a part of a system (GEPS); however, it was not tested well. We found that partial McMD did not work well for polylysine decapeptide and gave significantly worse sampling efficiency than a conventional GE. Herein, we elucidate the fundamental reason for this and propose a novel GEPS, adaptive lambda square dynamics (ALSD), which can resolve the problem faced when using partial McMD. We demonstrate that ALSD greatly increases the sampling efficiency over a conventional GE. We believe that ALSD is an effective method and is applicable to the conformational sampling of larger and more complicated biomolecule systems.

Aberrant gamma-band (30-80 Hz) oscillations may underlie cognitive deficits in schizophrenia (SZ). Gamma oscillations and their regulation by NMDA receptors can be studied via their evoked power (γEP) and phase locking (γPL) in response to auditory steady-state stimulation; these auditory steady-state responses (ASSRs) may be biomarkers for target engagement and early therapeutic effects. We previously reported that memantine, an NMDA receptor antagonist, enhanced two biomarkers of early auditory information processing: prepulse inhibition and mismatch negativity (MMN) in SZ patients and healthy subjects (HS). Here, we describe memantine effects on γEP and γPL in those subjects. SZ patients (n=18) and HS (n=14) received memantine 20 mg (p.o.) and placebo over 2 test days in a double-blind, randomized, counterbalanced, cross-over design. The ASSR paradigm (1 ms, 85 dB clicks in 250-0.5 s trains at a frequency of 40 Hz; 0.5 s inter-train interval) was used to assess γEP and γPL. SZ patients had reduced γEP and γPL; memantine enhanced γEP and γPL (p<0.025 and 0.002, respectively) in both SZ and HS. In patients, significant correlations between age and memantine effects were detected for γEP and γPL: greater memantine sensitivity on γEP and γPL were present in younger SZ patients, similar to our reported findings with MMN. Memantine acutely normalized cortical oscillatory dynamics associated with NMDA receptor dysfunction in SZ patients. Ongoing studies will clarify whether these acute changes predict beneficial clinical, neurocognitive and functional outcomes. These data support the use of gamma-band ASSR as a translational end point in pro-cognitive drug discovery and early-phase clinical trials.

Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world. However, little is known regarding the molecular mechanism of HCC development and progression and effective therapeutic methods. Recently, the granulin-epithelin precursor (GEP) was reported as a novel growth factor that can control HCC cell proliferation. Using the CAPSID program, we designed three small interfering RNAs (siRNAs) targeting the GEP gene (GEP-siRNA1, 2 and 3) and examined their tumor regression and suppression effects on cell proliferation. GEP-siRNA1 exhibited the strongest anti-proliferative effect among the GEP-siRNAs, in a time-dependent manner. To increase the biostability of the siRNA, we also constructed a short hairpin RNA (shRNA) using an H1/TO promoter with the same sequence of GEP-siRNA1 (GEP-shRNA). GEP-shRNA decreased the expression levels of GEP and tumor cell growth via cell cycle arrest at the G2/M stage and down-regulation of the cell proliferation proteins cyclin D1 and α-tubulin. Furthermore, GEP-shRNA inhibited tumor growth significantly after intratumoral injection into tumor-bearing Balb/C nude mice. Taken together, these results represent the first therapeutic application of RNA interference to GEP, which is a promising target molecule for HCC treatment, as an approach for the suppression of HCC cell proliferation.

OBJECTIVE

Improved understanding of risk of recurrence (ROR) is needed to reduce cases of recurrence and more effectively treat breast cancer patients. The purpose of this study was to examine how a gene-expression profile (GEP), identified by Prosigna, influences physician adjuvant treatment selection for early breast cancer (EBC) and the effects of this influence on optimizing adjuvant treatment recommendations in clinical practice.

METHODS

A prospective, observational, multicenter study was carried out in 15 hospitals across Spain. Participating medical oncologists completed pre-assessment, post-assessment, and follow-up questionnaires recording their treatment recommendations and confidence in these recommendations, before and after knowing the patient's ROR. Patients completed questionnaires on decision-making, anxiety, and health status.

RESULTS

Between June 2013 and January 2014, 217 patients enrolled and a final 200 were included in the study. Patients were postmenopausal, estrogen receptor positive, human epidermal growth hormone factor negative, and node negative with either stage 1 or stage 2 tumors. After receiving the GEP results, treatment recommendations were changed for 40 patients (20%). The confidence of medical oncologists in their treatment recommendations increased in 41.6% and decreased in 6.5% of total cases. Patients reported lower anxiety after physicians made treatment recommendations based on the GEP results (p < 0.05).

CONCLUSIONS

Though this study does not include evaluation of the impact of GEP on long-term outcomes, it was found that GEP results influenced the treatment decisions of medical oncologists and their confidence in adjuvant therapy selection. Patients' anxiety about the selected adjuvant therapy decreased with use of the GEP.

In 2014, the Shizuoka Cancer Center launched project High‑tech Omics‑based Patient Evaluation (HOPE), which features whole exome sequencing (WES) and gene expression profiling (GEP) of fresh surgical specimens from cancer patients. With the development of clinical trials of programmed death‑1 (PD‑1)/PD‑ligand 1 (PD‑L1) blockade, PD‑L1 expression and a high tumor mutation burden become possible biomarkers that could be used to predict immune responses. In this study, based on WES and GEP data from 1,734 tumors from the HOPE project, we established a tumor microenvironment (TME) immune‑type classification consisting of 4 types to evaluate the immunological status of cancer patients and analyze immunological pathways specific for immune types. Project HOPE was conducted in accordance with the Ethical Guidelines for Human Genome and Genetic Analysis Research with the approval of the Institutional Review Board. Based on the expression level of the PD‑L1 and CD8B genes, the immunological status was divided into 4 types as follows: A, PD‑L1+CD8B+; B, PD‑L1+CD8B‑; C, PD‑L1‑CD8B‑; and D, PD‑L1‑CD8B+. Type A, with PD‑L1+ and CD8B+, exhibited an upregulation of cytotoxic T lymphocyte (CTL) killing‑associated genes, T‑cell activation genes, antigen‑presentation and dendritic cell (DC) maturation genes, and T‑cell‑attracting chemokine genes, which promoted Th1 antitumor responses. By contrast, type C, with PD‑L1‑ and CD8B‑, exhibited a low expression of T‑cell‑activating genes and an upregulation of cancer driver gene signaling, which suggested an immune‑suppressive status. With regard to hypermutator tumors, PD‑L1+ hypermutator cases exhibited a specific upregulation of the IL6 gene compared with the PD‑L1‑ cases. On the whole, our data indicate that the classification of the TME immune types may prove to be a useful tool for evaluating the immunological status and predicting antitumor responses and prognosis.

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) comprise a heterogeneous group of malignancies often presenting with metastasis at diagnosis and whose clinical outcome is difficult to predict. Somatostatin (SST) analogs (SSAs) provide a valuable pharmacological tool to palliate hormonal symptoms, and control progression in some NETs. However, many patients do not respond to SSAs or develop resistance, and there are many uncertainties regarding pathophysiology of SST and its receptors (sst1-sst5) in GEP-NETs.

The expression of SST system components in GEP-NETs was determined, compared with that of non-tumor adjacent and normal tissues and correlated with clinical and histological characteristics. Specifically, 58 patients with GEP-NETs and 14 normal samples were included. Cell viability in NET cell lines was determined in response to specific SSAs.

Normal samples and non-tumor adjacent tissues presented a similar expression profile, with appreciable expression of sst2 and sst3, and a lower expression of the other receptors. In contrast, cortistatin, sst1, sst4, and sst5 were overexpressed in tumors, while sst3 and sst4 seemed overexpressed in less differentiated tumors. Some SST system components were related to vascular/nerve invasion and metastasis. In vitro, sst1 and sst3 agonists reduced viability in BON-1 cells, while they, similar to octreotide and pasireotide, increased viability in QGP-1 cells.

These results provide novel information on SST system pathophysiology in GEP-NETs, including relevant associations with clinical-histological parameters, which might help to better understand the intrinsic heterogeneity of NETs and to identify novel biomarkers and/or targets with potential prognostic and/or therapeutic value for GEP-NETs patients.

Stamen is a unique plant organ wherein germ cells or microsporocytes that commit to meiosis are initiated from somatic cells during its early developmental process. While genes determining stamen identity are known according to the ABC model of floral development, little information is available on how these genes affect germ cell initiation. By using the Affymetrix GeneChip Rice Genome Array to assess 51 279 transcripts, we established a dynamic gene expression profile (GEP) of the early developmental process of rice (Oryza sativa) stamen. Systematic analysis of the GEP data revealed novel expression patterns of some developmentally important genes including meiosis-, tapetum-, and phytohormone-related genes. Following the finding that a substantial amount of nuclear genes encoding photosynthetic proteins are expressed at the low levels in early rice stamen, through the ChIP-seq analysis we found that a C-class MADS box protein, OsMADS58, binds many nuclear-encoded genes participated in photosystem and light reactions and the expression levels of most of them are increased when expression of OsMADS58 is downregulated in the osmads58 mutant. Furthermore, more pro-chloroplasts are observed and increased signals of reactive oxygen species are detected in the osmads58 mutant anthers. These findings implicate a novel link between stamen identity determination and hypoxia status establishment.

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) refer to a group of heterogeneous cancers of neuroendocrine cell phenotype that mainly fall into one of two subtypes: gastroenteropancreatic neuroendocrine tumors (GEP-NETs; well differentiated) or gastroenteropancreatic neuroendocrine carcinomas (GEP-NECs; poorly differentiated). Although originally defined as orphan cancers, their steadily increasing incidence highlights the need to better understand their etiology. Accumulating epidemiological and clinical data have shed light on the pathological characteristics of these diseases. However, the relatively low number of patients has hampered conducting large-scale clinical trials and hence the development of novel treatment strategies. To overcome this limitation, tractable disease models that faithfully reflect clinical features of these diseases are needed. In this Review, we summarize the current understanding of the genetics and biology of these diseases based on conventional disease models, such as genetically engineered mouse models (GEMMs) and cell lines, and discuss the phenotypic differences between the models and affected humans. We also highlight the emerging disease models derived from human clinical samples, including patient-derived xenograft models and organoids, which may provide biological and therapeutic insights into GEP-NENs.

BACKGROUND

Multiple endocrine neoplasia type 1 (MEN-1) is an autosomal dominant tumor syndrome associated with parathyroid, gastroenteropancreatic (GEP), and pituitary neoplasia. Gastrinoma and GEP malignancy are common life-threatening endocrine complications of MEN-1. An effective management strategy for these disorders remains to be determined. The authors attempted to determine the role of the somatostatin analogue, octreotide, in ameliorating features of hypergastrinemic GEP neoplasia associated with MEN-1.

METHODS

Five MEN-1 patients with hypergastrinemia and either symptoms of GEP neoplasia or hepatic metastases received a trial of octreotide, 100 microg subcutaneously, three times daily for 3 months.

RESULTS

Treatment with octreotide was associated with a rapid symptomatic and biochemical response. In all patients serum gastrin fell to < 25% of the pretreatment value. The serum glycoprotein-alphasubunit (a marker of enterochromaffin-like [ECL] cell hyperplasia, gastric carcinoidosis, and disseminated enteropancreatic malignancy) was elevated at baseline in three patients. In each case the serum glycoprotein-alphasubunit normalized after treatment with octreotide. Hepatic metastases were present in two patients at baseline. The size of the metastases diminished by up to 15% during the period of octreotide treatment. Four patients reported symptoms prior to treatment: lethargy, easy fatigability, and generalized musculoskeletal discomfort. A marked symptomatic improvement occurred in each case. No patient experienced side effects related to octreotide therapy and all elected to remain on treatment after completion of the trial.

CONCLUSIONS

Octreotide is a safe and effective adjunct to surgical strategies for the management of GEP neoplasia in hypergastrinemic MEN-1 patients.

Although previously considered rare, recent epidemiological studies have revealed that the incidence (3.6/100,000) and prevalence (35/100,000) of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) has increased over the past few decades. Despite the progress in the understanding of GEP-NET molecular biology, there is still little advance in the early diagnosis due to lack of specific tumor markers. As the tumors are mostly detected in their late stage, they are not well controlled by either biotherapy or conventional chemotherapy, and thus represent a significant clinical issue. Chronic inflammation has been implicated in the development of GEP-NETs. This review presents recent findings that link pro-inflammatory cytokines to the molecular basis of GEP-NET tumorigenesis, leading to a more personalized approach to disease management and therapy.

Purpose of review: The purpose of our review is to explore global epidemiologic trends of gastroenteropancreatic (GEP) neuroendocrine tumors (NETs). Specifically, we sought to examine whether there are differences in incidence, prevalence, distribution (by primary tumor site, tumor grade, tumor stage at presentation), and overall survival of GEP NETs between different regions of the world.

Recent findings: GEP NET incidence rates are rising steadily in North America, Asia, and Europe, though this rise appears to be most profound in North America. The distribution of GEP NETs differs regionally as in North America small intestinal and rectal NETs are most prevalent, in Asia rectal and pancreatic NETs are most prevalent, and in Europe small intestinal and pancreatic NETs are most prevalent. Overall survival for patients with GEP NETs appears to be improving with time. Some of the global increase in GEP NET incidence can be explained by increased health care utilization. This factor alone, however, does not explain the rise completely. Population-based studies utilizing uniform data collection instruments and a standard pathologic grading system are needed to identify other factors which may be contributing to this phenomenon.

Keywords: Gastroenteropancreatic neuroendocrine neoplasms; Global epidemiology; Incidence; Neuroendocrine carcinoma; Neuroendocrine tumors; Prevalence.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity with remarkably variable clinical outcome. Gene expression profiling (GEP) classifies DLBCL into activated B-cell like (ABC), germinal center B-cell like (GCB), and Type-III subtypes, with ABC-DLBCL characterized by a poor prognosis and constitutive NF-κB activation. A major challenge for the application of this cell of origin (COO) classification in routine clinical practice is to establish a robust clinical assay amenable to routine formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies. In this study, we investigated the possibility of COO-classification using FFPE tissue RNA samples by massive parallel quantitative reverse transcription PCR (qRT-PCR). We established a protocol for parallel qRT-PCR using FFPE RNA samples with the Fluidigm BioMark HD system, and quantified the expression of the COO classifier genes and the NF-κB targeted-genes that characterize ABC-DLBCL in 143 cases of DLBCL. We also trained and validated a series of basic machine-learning classifiers and their derived meta classifiers, and identified SimpleLogistic as the top classifier that gave excellent performance across various GEP data sets derived from fresh-frozen or FFPE tissues by different microarray platforms. Finally, we applied SimpleLogistic to our data set generated by qRT-PCR, and the ABC and GCB-DLBCL assigned showed the respective characteristics in their clinical outcome and NF-κB target gene expression. The methodology established in this study provides a robust approach for DLBCL sub-classification using routine FFPE diagnostic biopsies in a routine clinical setting.

Identifying the best gene expression pattern associated with low-risk disease in patients with newly diagnosed multiple myeloma (MM) is important to direct clinical treatments. The MM Survival Index14 (MMSI14) was developed from GEP data sets of 22 normal plasma cells (NPC), 5 MM cell lines (MMCL), 44 monoclonal gammopathy of undetermined significance (MGUS), and 351 newly diagnosed MM patients. R/bioconductor and siggenes package were used to obtain heatmap, boxplot and histogram whose results were then analyzed by Kaplan-Meier analysis. Fourteen genes associated with low-risk disease in MM were identified. We validated the disease prognostic power of MMSI14 with an independent data set of other 214 newly diagnosed MM patients and also compared our model with the 70-gene, the 8-subgroup, IFM15, and HMCLs7 models. Survival analysis showed that a low MMSI14 signature was associated with longer survival. Applying MMSI14 to independent data sets, we were able to classify 39% of patients as low-risk, with a survival probability of more than 90% at 60 months. Multiple clinical parameters confirmed significant correlation between low- and high-risk subgroups defined by MMSI14. Comparing previously published models to the same data sets the MMSI14 model retained the best prognostic value. We have developed a new gene model (MMSI14) for defining low-risk, newly diagnosed MM. The multivariate comparative analysis confirmed that MMSI14 is the best available model to predict clinical outcome in MM patients.

The two major subtypes of diffuse large B-cell lymphoma (DLBCL) (germinal centre B-cell - like (GCB-DLBCL) and activated B-cell - like (ABC-DLBCL)) are defined by means of gene expression profiling (GEP). Patients with GCB-DLBCL survive longer with the current standard regimen R-CHOP than patients with ABC-DLBCL. As GEP is not part of the current routine diagnostic work-up, efforts have been made to find a substitute than involves immunohistochemistry (IHC). Various algorithms achieved this with 80-90% accuracy. However, conflicting results on the appropriateness of IHC have been reported. Because it is likely that the molecular subtypes will play a role in future clinical practice, we assessed the determination of the molecular DLBCL subtypes by means of IHC at our University Hospital, and some aspects of this determination elsewhere in Switzerland. The most frequently used Hans algorithm includes three antibodies (against CD10, bcl-6 and MUM1). From records of the routine diagnostic work-up, we identified 51 of 172 (29.7%) newly diagnosed and treated DLBCL cases from 2005 until 2010 with an assigned DLBCL subtype. DLBCL subtype information was expanded by means of tissue microarray analysis. The outcome for patients with the GCB subtype was significantly better compared with those with the non-GC subtype, independent of the age-adjusted International Prognostic Index. We found a lack of standardisation in the subtype determination by means of IHC in Switzerland and significant problems of reproducibility. We conclude that the Hans algorithm performs well in our hands and that awareness of this important matter is increasing. However, outside clinical trials, vigorous efforts to standardise IHC determination are needed as DLBCL subtype-specific therapies emerge.

Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: hierarchical clustering, K-means clustering, and multivariate mixture model-based clustering. Using several methods to measure agreement, between-cluster isolation, and withincluster coherence, such as the Adjusted Rand Index, the Pseudo F test, the r(2) test, and the profile plot, we have assessed the effectiveness of kernel density clustering for recovering clusters, and its robustness against noise on clustering both simulated and real GEP data. Our results show that the kernel density clustering method has excellent performance in recovering clusters from simulated data and in grouping large real expression profile data sets into compact and well-isolated clusters, and that it is the most robust clustering method for analysing noisy expression profile data compared to the other three methods assessed.

Small GTPases are converted from the GDP-bound inactive form to the GTP-bound active form by a GDP/GTP exchange reaction which is regulated by GDP/GTP exchange proteins (GEPs). We have found both stimulatory and inhibitory GEPs, which we have named GDP dissociation stimulators (GDSs) and GDP dissociation inhibitors (GDIs) respectively. We have isolated Smg GDS, Rho GDI and Rab GDI, cloned them, and determined their primary structures. These GEPs are active on a group of small GTPases: Smg GDS on at least K-Ras, Rap1/Smg21, Rho and Rac; Rho GDI on at least Rho, Rac and Cdc42; Rab GDI on most of the Rab family members. These GEPs have an additional function, regulating the translocation of their substrate small GTPases between the membrane and the cytosol. The GEPs interact only with the post-translationally modified form of their substrate small GTPases.

Longevity as a complex life-history trait shares an ontogenetic relationship with other quantitative traits and varies among individuals, families and populations. Heritability estimates of longevity suggest that about a third of the phenotypic variation associated with the trait is attributable to genetic factors, and the rest is influenced by epigenetic and environmental factors. Individuals react differently to the environments that they are a part of, as well as to the environments they construct for their survival and reproduction; the latter phenomenon is known as niche construction. Lifestyle influences longevity at all the stages of development and levels of human diversity. Hence, lifestyle may be viewed as a component of niche construction. Here, we: a) interpret longevity using a combination of genotype-epigenetic-phenotype (GEP) map approach and niche-construction theory, and b) discuss the plausible influence of genetic and epigenetic factors in the distribution and maintenance of longevity among individuals with normal life span on the one hand, and centenarians on the other. Although similar genetic and environmental factors appear to be common to both of these groups, exceptional longevity may be influenced by polymorphisms in specific genes, coupled with superior genomic stability and homeostatic mechanisms, maintained by negative frequency-dependent selection. We suggest that a comparative analysis of longevity between individuals with normal life span and centenarians, along with insights from population ecology and evolutionary biology, would not only advance our knowledge of biological mechanisms underlying human longevity, but also provide deeper insights into extending healthy life span.

Lymphoma classification has changed several times over time as our understanding of normal and malignant lymphocyte biology has advanced. This has improved prognostication, but there remain large diagnostic groups with diverse outcomes. In an attempt to refine diagnosis and prognostic power in these, global gene expression profiling (GEP) has been used to further improve our understanding of lymphoma. This review will cover the impact of GEP on the diagnosis, prognosis, biological understanding and identification of novel treatments for the main types of lymphoma, as well its translation to clinical practice. Specifically, it will cover the use of GEP to identify prognostic subgroups within existing diagnostic categories, in an attempt to improve prognostication in those subgroups with wide variation in outcome. Many of these studies have given additional novel insights into the biology of lymphoma, including the role of the immune system and the stromal environment. The improved understanding that these studies have given have suggested possible new treatments, linking diagnosis, prognosis, biological understanding and improved treatment.

The widespread availability and reliability of immunohistochemical techniques in the last three decades have allowed researchers to identify cells with common neuroendocrine markers in virtually every organ. As a whole, these neuroendocrine cells form the so-called diffuse neuroendocrine system. Tumours arising from the cells of the diffuse neuroendocrine system are defined as (neuro)endocrine tumours (NETs). NETs have been increasingly described in recent years. However, despite the increase in the number of published papers focused on NET, we still lack adequate epidemiological data, particularly for non-gastroenteropancreatic (GEP) NETs. Furthermore, the real incidence of neuroendocrine differentiation for most sites is not completely known and is probably underestimated. As a consequence, data on the clinical features of many NET subgroups are not well known or confusing. For all of these reasons, we have attempted to evaluate the epidemiology of non-GEP NETs, reviewing the limited data available in the literature.

The present study reported the growth and metabolism characteristics of anaerobic ammonium-oxidizing (anammox) bacteria aggregates in an expanded granular sludge bed (EGSB). The results showed that the anammox bacteria aggregates presented starvation, growth, and inhibition phase along with the increase of substrate supply. The substrate conversion rates for survival were 0.05 kgNH4(+)-N/(kgVSS·day), 0.07 kgNO2(-)-N/(kgVSS·day), and 0.12 kgN/(kgVSS·day); the substrate conversion rates for maximum growth were 0.21 kgNH4(+)-N/(kgVSS·day), 0.24 kgNH4(+)-N/(kgVSS·day), and 0.45 kgNH4(+)-N/(kgVSS·day), respectively. In the growth phase, the yield of anammox bacteria aggregates was 0.14 gVSS/(gNH4(+)-N), 0.12 gVSS/(gNO2(-)-N), and 0.70 gVSS/(gNO3(-)-N); the yield of extracellular polymeric substances (EPS) was 0.11 gEPS/(gNH4(+)-N), 0.09 gEPS/(gNO2(-)-N), and 0.55 gEPS/(gNO3(-)-N), respectively. The EPS contents in anammox bacteria aggregates were high compared to that in anaerobic granular sludge. Speculated from the cell yield, the energy for anammox bacteria growth was not only from nitrite oxidation, but also from anammox reaction.

The localization of the gastro-entero-pancreatic (GEP) endocrine cells in the flatfish, Paralichtys olivaceus was examined using immunocytochemical methods. The Brockmann body of the flatfish included a large principal islet and a smaller islet. Three types of endocrine cells, i.e., insulin-, glucagon- and somatostatin-immunoreactive cells were found in both islets. Pancreatic polypeptide (PP)-immunoreactive cells were restricted to the periphery of the smaller islet. In the digestive tract, somatostatin cells occurred only in the stomach. The pyloric appendages contained cells reactive simultaneously to cholecystokinin (CCK) antiserum and to gastrin antiserum, whereas the middle portion of the intestine contained cells reactive only to the CCK antiserum. The intestinal endocrine cells showing N-terminal glucagon-immunoreactivity were also reactive to a glicentin antiserum.

Gene expression profiling (GEP) enables the simultaneous investigation of the expression of tens of thousands of genes and was successfully introduced in leukaemia research a decade ago. Aiming to better understand the diversity of genetic aberrations in acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL), pioneer studies investigated and confirmed the predictability of many cytogenetic and molecular subclasses in AML and ALL. In addition, GEP can define new prognostic subclasses within distinct leukaemia subgroups, as illustrated in AML with normal karyotype. Another approach is the development of treatment-specific sensitivity assays, which might contribute to targeted therapy studies. Finally, GEP might enable the detection of new molecular targets for therapy in patients with acute leukaemia. Meanwhile, large multicentre studies, e.g. the Microarray Innovations in LEukaemia (MILE) study, prepare for a standardised introduction of GEP in leukaemia diagnostic algorithms, aiming to translate this novel methodology into clinical routine for the benefit of patients with the complex disorders of AML and ALL.

BACKGROUND

T-cell acute lymphoblastic leukemia (T-ALL) is a genetically heterogeneous disease with the need for treatment optimization. Previously, high expression of Insulin-like growth factor binding protein 7 (IGFBP7), a member of the IGF system, was identified as negative prognostic factor in adult T-ALL patients. Since aberrant IGFBP7 expression was observed in a variety of neoplasia and was relevant for prognosis in T-ALL, we investigated the functional role of IGFBP7 in Jurkat and Molt-4 cells as in vitro models for T-ALL.

METHODS

Jurkat and Molt-4 cells were stably transfected with an IGFBP7 over-expression vector or the empty vector as control. Proliferation of the cells was assessed by WST-1 assays and cell cycle status was measured by flow-cytometry after BrDU/7-AAD staining. The effect of IGFBP7 over-expression on sensitivity to cytostatic drugs was determined in AnnexinV/7-AAD assays. IGF1-R protein expression was measured by Western Blot and flow-cytometric analysis. IGF1-R associated gene expression profiles were generated from microarray gene expression data of 86 T-ALL patients from the Microarrays Innovations in Leukemia (MILE) multicenter study.

RESULTS

IGFBP7-transfected Jurkat cells proliferated less, leading to a longer survival in a nutrient-limited environment. Both IGFBP7-transfected Jurkat and Molt-4 cells showed an arrest in the G0/G1 cell cycle phase. Furthermore, Jurkat IGFBP7-transfected cells were resistant to vincristine and asparaginase treatment. Surface expression and whole protein measurement of IGF1-R protein expression showed a reduced abundance of the receptor after IGFBP7 transfection in Jurkat cells. Interestingly, combination of the IGF1-R inhibitor NPV-AEW541 restored sensitivity to vincristine in IGFBP7-transfected cells. Additionally, IGF1-R associated GEP revealed an up-regulation of important drivers of T-ALL pathogenesis and regulators of chemo-resistance and apoptosis such as NOTCH1, BCL-2, PRKCI, and TP53.

CONCLUSIONS

This study revealed a proliferation inhibiting effect of IGFBP7 by G0/G1 arrest and a drug resistance-inducing effect of IGFBP7 against vincristine and asparaginase in T-ALL. These results provide a model for the previously observed association between high IGFBP7 expression and chemotherapy failure in T-ALL patients. Since the resistance against vincristine was abolished by IGF1-R inhibition, IGFBP7 could serve as biomarker for patients who may benefit from therapies including IGF1-R inhibitors in combination with chemotherapy.

Rab3A, a member of the Rab3 small GTP-binding protein (G protein) family, regulates Ca(2+)-dependent exocytosis of neurotransmitter. Rab3A cycles between the GDP-bound inactive and GTP-bound active forms, and the former is converted to the latter by the action of a GDP/GTP exchange protein (GEP). We have previously purified a GEP from rat brain with lipid-modified Rab3A as a substrate. Purified Rab3 GEP is active on all the Rab3 subfamily members including Rab3A, -3B, -3C, and -3D. Purified Rab3 GEP is active on the lipid-modified form, but not on the lipid-unmodified form. Purified Rab3 GEP is inactive on Rab3A complexed with Rab GDI. The recombinant protein is prepared from the Rab3 GEP-expressed Spodoptera frugiperda cells (Sf9 cells). The properties of recombinant Rab3 GEP, including the requirement for lipid modifications of Rab3A, the substrate specificity, and the sensitivity to Rab GDI, are similar to those of purified Rab3 GEP. Overexpression of Rab3 GEP inhibits Ca(2+)-dependent exocytosis from PC12 cells. On the other hand, Rab3 GEP is identical to a protein named DENN/MADD: differentially expressed in normal versus neoplastic (DENN)/mitogen-activated protein kinase-activating death domain (MADD). Here, we describe the purification method for recombinant Rab3 GEP from Sf9 cells and the functional properties of Rab3 GEP in Ca(2+)-dependent exocytosis by use of the human growth hormone coexpression assay system of PC12 cells.