Spindle and kinetochore-related complex subunit 3 has a protumour function in osteosarcoma by activating the Notch pathway.

Increasing expression of spindle and kinetochore-related complex subunit 3 (SKA3) is related to the progression of multiple malignancies. However, the role of SKA3 in osteosarcoma remains unexplored. The present study aimed to investigate the relevance of SKA3 in osteosarcoma. Preliminarily, SKA3 expression in osteosarcoma was assessed through The Cancer Genome Atlas (TCGA) analysis, which revealed high levels of SKA3 transcripts in osteosarcoma tissues. Subsequent examination of clinical tissues confirmed the abundant expression of SKA3 in osteosarcoma. Downregulation of SKA3 expression in osteosarcoma cell lines resulted in repressive effects on cell proliferation, migration, invasion, and epithelial-to-mesenchymal transition (EMT), while upregulation of SKA3 expression had the opposite effect. Gene set enrichment analysis (GSEA) revealed that the Notch pathway is enriched in SKA3 high groups based on different expressed genes from the TCGA data. Further investigation showed that the levels of Notch1, Notch1 intracellular domain (NICD1), hairy and enhancer of split 1 (HES1), and hairy/enhancer-of-split related with YRPW motif protein 1 (HEY1) were downregulated in SKA3-silenced osteosarcoma cells, and upregulated in SKA3-overexpressed osteosarcoma cells. Activation of the Notch pathway by increasing NICD1 expression reversed the antitumour effects induced by SKA3 silencing, while deactivation of the Notch pathway diminished the protumour effects induced by SKA3 overexpression. Moreover, SKA3-silenced osteosarcoma cells exhibited a reduced capacity for xenograft formation in nude mice. In conclusion, SKA3 plays a cancer-enhancing role in osteosarcoma through its effect on the Notch pathway. Reducing the expression of SKA3 could be a potential therapeutic approach for treating osteosarcoma.

Minimally Invasive Mitral Valve Surgery With Concomitant Cox Maze Procedure Is as Effective as a Median Sternotomy With Decreased Morbidity.

OBJECTIVE: A right minithoracotomy (RMT) is a minimally invasive surgical approach that has been increasingly performed for the concomitant Cox maze IV procedure (CMP) and mitral valve surgery (MVS). Little is known regarding whether long-term rhythm and survival outcomes are affected by the RMT as compared with the traditional median sternotomy (MS) approach. METHODS: Between April 2004 and April 2021, 377 patients underwent the concomitant CMP and MVS, of whom 38% had RMT. Propensity score matching yielded 116 pairs. Freedom from atrial tachyarrhythmias (ATA) was assessed with prolonged monitoring annually for 8 years. Survival, rhythm, and perioperative outcomes were compared. RESULTS: The unmatched RMT cohort had a greater freedom from ATA recurrence at 1 year (99% vs 90%, P = 0.001) and 3 years (94% vs 86%, P = 0.045). The matched RMT cohort had longer cardiopulmonary bypass (median: 215 [199 to 253] vs 170 [136 to 198] min, P < 0.001) and aortic cross-clamp (110 [98 to 124] vs 86 [71 to 102] min, P < 0.001) times but shorter intensive care time (48 [24 to 95] vs 71 [26 to 144] h, P = 0.001) and length of stay (8 [6 to 11] vs 10 [7 to 14] h, P < 0.001). More pacemakers (18% vs 4%, P < 0.001) and postoperative transfusions (57% vs 41%, P = 0.014) occurred in the MS cohort. The 30-day mortality (P = 0.651) and 8-year survival (P = 0.072) was not significantly different between the cohorts. CONCLUSIONS: Early 1-year and 3-year freedom from ATA recurrence was better in the RMT cohort compared with the MS cohort. Despite longer operative times, the RMT cohort had shorter lengths of stay, fewer postoperative transfusions, and fewer pacemakers placed.

Identifying molecular phenotypes in sepsis: an analysis of two prospective observational cohorts and secondary analysis of two randomised controlled trials.

BACKGROUND: In sepsis and acute respiratory distress syndrome (ARDS), heterogeneity has contributed to difficulty identifying effective pharmacotherapies. In ARDS, two molecular phenotypes (hypoinflammatory and hyperinflammatory) have consistently been identified, with divergent outcomes and treatment responses. In this study, we sought to derive molecular phenotypes in critically ill adults with sepsis, determine their overlap with previous ARDS phenotypes, and evaluate whether they respond differently to treatment in completed sepsis trials. METHODS: We used clinical data and plasma biomarkers from two prospective sepsis cohorts, the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study (N=1140) and the Early Assessment of Renal and Lung Injury (EARLI) study (N=818), in latent class analysis (LCA) to identify the optimal number of classes in each cohort independently. We used validated models trained to classify ARDS phenotypes to evaluate concordance of sepsis and ARDS phenotypes. We applied these models retrospectively to the previously published Prospective Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis and Septic Shock (PROWESS-SHOCK) trial and Vasopressin and Septic Shock Trial (VASST) to assign phenotypes and evaluate heterogeneity of treatment effect. FINDINGS: A two-class model best fit both VALID and EARLI (p<0·0001). In VALID, 804 (70·5%) of the 1140 patients were classified as hypoinflammatory and 336 (29·5%) as hyperinflammatory; in EARLI, 530 (64·8%) of 818 were hypoinflammatory and 288 (35·2%) hyperinflammatory. We observed higher plasma pro-inflammatory cytokines, more vasopressor use, more bacteraemia, lower protein C, and higher mortality in the hyperinflammatory than in the hypoinflammatory phenotype (p<0·0001 for all). Classifier models indicated strong concordance between sepsis phenotypes and previously identified ARDS phenotypes (area under the curve 0·87-0·96, depending on the model). Findings were similar excluding participants with both sepsis and ARDS. In PROWESS-SHOCK, 1142 (68·0%) of 1680 patients had the hypoinflammatory phenotype and 538 (32·0%) had the hyperinflammatory phenotype, and response to activated protein C differed by phenotype (p=0·0043). In VASST, phenotype proportions were similar to other cohorts; however, no treatment interaction with the type of vasopressor was observed (p=0·72). INTERPRETATION: Molecular phenotypes previously identified in ARDS are also identifiable in multiple sepsis cohorts and respond differently to activated protein C. Molecular phenotypes could represent a treatable trait in critical illness beyond the patient's syndromic diagnosis. FUNDING: US National Institutes of Health.

MS4A4A modifies the risk of Alzheimer disease by regulating lipid metabolism and immune response in a unique microglia state.

Genome-wide association studies (GWAS) have identified many modifiers of Alzheimer disease (AD) risk enriched in microglia. Two of these modifiers are common variants in the MS4A locus (rs1582763: protective and rs6591561: risk) and serve as major regulators of CSF sTREM2 levels. To understand their functional impact on AD, we used single nucleus transcriptomics to profile brains from carriers of these variants. We discovered a "chemokine" microglial subpopulation that is altered in MS4A variant carriers and for which MS4A4A is the major regulator. The protective variant increases MS4A4A expression and shifts the chemokine microglia subpopulation to an interferon state, while the risk variant suppresses MS4A4A expression and reduces this subpopulation of microglia. Our findings provide a mechanistic explanation for the AD variants in the MS4A locus. Further, they pave the way for future mechanistic studies of AD variants and potential therapeutic strategies for enhancing microglia resilience in AD pathogenesis.

Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis.

BACKGROUND: Two acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. METHODS: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. FINDINGS: The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90-0·95) in EARLI and 0·88 (0·84-0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81-0·94] vs 0·92 [0·88-0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). INTERPRETATION: Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. FUNDING: US National Institutes of Health and European Society of Intensive Care Medicine.

Latent Class Analysis Reveals COVID-19-related Acute Respiratory Distress Syndrome Subgroups with Differential Responses to Corticosteroids.

Rationale: Two distinct subphenotypes have been identified in acute respiratory distress syndrome (ARDS), but the presence of subgroups in ARDS associated with coronavirus disease (COVID-19) is unknown. Objectives: To identify clinically relevant, novel subgroups in COVID-19-related ARDS and compare them with previously described ARDS subphenotypes. Methods: Eligible participants were adults with COVID-19 and ARDS at Columbia University Irving Medical Center. Latent class analysis was used to identify subgroups with baseline clinical, respiratory, and laboratory data serving as partitioning variables. A previously developed machine learning model was used to classify patients as the hypoinflammatory and hyperinflammatory subphenotypes. Baseline characteristics and clinical outcomes were compared between subgroups. Heterogeneity of treatment effect for corticosteroid use in subgroups was tested. Measurements and Main Results: From March 2, 2020, to April 30, 2020, 483 patients with COVID-19-related ARDS met study criteria. A two-class latent class analysis model best fit the population (P = 0.0075). Class 2 (23%) had higher proinflammatory markers, troponin, creatinine, and lactate, lower bicarbonate, and lower blood pressure than class 1 (77%). Ninety-day mortality was higher in class 2 versus class 1 (75% vs. 48%; P < 0.0001). Considerable overlap was observed between these subgroups and ARDS subphenotypes. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR cycle threshold was associated with mortality in the hypoinflammatory but not the hyperinflammatory phenotype. Heterogeneity of treatment effect to corticosteroids was observed (P = 0.0295), with improved mortality in the hyperinflammatory phenotype and worse mortality in the hypoinflammatory phenotype, with the caveat that corticosteroid treatment was not randomized. Conclusions: We identified two COVID-19-related ARDS subgroups with differential outcomes, similar to previously described ARDS subphenotypes. SARS-CoV-2 PCR cycle threshold had differential value for predicting mortality in the subphenotypes. The subphenotypes had differential treatment responses to corticosteroids.

Hemispheric CSF volume ratio quantifies progression and severity of cerebral edema after acute hemispheric stroke.

As swelling occurs, CSF is preferentially displaced from the ischemic hemisphere. The ratio of CSF volume in the stroke-affected hemisphere to that in the contralateral hemisphere may quantify the progression of cerebral edema. We automatically segmented CSF from 1,875 routine CTs performed within 96 hours of stroke onset in 924 participants of a stroke cohort study. In 737 subjects with follow-up imaging beyond 24-hours, edema severity was classified as affecting less than one-third of the hemisphere (CED-1), large hemispheric infarction (LHI, over one-third the hemisphere), without midline shift (CED-2) or with midline shift (CED-3). Malignant edema was LHI resulting in deterioration, requiring osmotic therapy, surgery, or resulting in death. Hemispheric CSF ratio was lower on baseline CT in those with LHI (0.91 vs. 0.97, p < 0.0001) and decreased more rapidly in those with LHI who developed midline shift (0.01 per hour for CED-3 vs. 0.004/hour CED-2). The ratio at 24-hours was lower in those with midline shift (0.41, IQR 0.30-0.57 vs. 0.66, 0.56-0.81 for CED-2). A ratio below 0.50 provided 90% sensitivity, 82% specificity for predicting malignant edema among those with LHI (AUC 0.91, 0.85-0.96). This suggests that the hemispheric CSF ratio may provide an accessible early biomarker of edema severity.

A large-scale genome-wide association study meta-analysis of cannabis use disorder.

BACKGROUND: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. METHODS: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. FINDINGS: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. INTERPRETATION: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder. FUNDING: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

Self-Reporting Transposons Enable Simultaneous Readout of Gene Expression and Transcription Factor Binding in Single Cells.

Cellular heterogeneity confounds in situ assays of transcription factor (TF) binding. Single-cell RNA sequencing (scRNA-seq) deconvolves cell types from gene expression, but no technology links cell identity to TF binding sites (TFBS) in those cell types. We present self-reporting transposons (SRTs) and use them in single-cell calling cards (scCC), a novel assay for simultaneously measuring gene expression and mapping TFBS in single cells. The genomic locations of SRTs are recovered from mRNA, and SRTs deposited by exogenous, TF-transposase fusions can be used to map TFBS. We then present scCC, which map SRTs from scRNA-seq libraries, simultaneously identifying cell types and TFBS in those same cells. We benchmark multiple TFs with this technique. Next, we use scCC to discover BRD4-mediated cell-state transitions in K562 cells. Finally, we map BRD4 binding sites in the mouse cortex at single-cell resolution, establishing a new method for studying TF biology in situ.

A viral toolkit for recording transcription factor-DNA interactions in live mouse tissues.

Transcription factors (TFs) enact precise regulation of gene expression through site-specific, genome-wide binding. Common methods for TF-occupancy profiling, such as chromatin immunoprecipitation, are limited by requirement of TF-specific antibodies and provide only end-point snapshots of TF binding. Alternatively, TF-tagging techniques, in which a TF is fused to a DNA-modifying enzyme that marks TF-binding events across the genome as they occur, do not require TF-specific antibodies and offer the potential for unique applications, such as recording of TF occupancy over time and cell type specificity through conditional expression of the TF-enzyme fusion. Here, we create a viral toolkit for one such method, calling cards, and demonstrate that these reagents can be delivered to the live mouse brain and used to report TF occupancy. Further, we establish a Cre-dependent calling cards system and, in proof-of-principle experiments, show utility in defining cell type-specific TF profiles and recording and integrating TF-binding events across time. This versatile approach will enable unique studies of TF-mediated gene regulation in live animal models.

PTPN14, a target gene of miR-4295, restricts the growth and invasion of osteosarcoma cells through inactivation of YAP1 signalling.

Non-receptor tyrosine phosphatase 14 (PTPN14) has emerged as a novel tumour-suppressor in a wide range of human cancer types. However, the role of PTPN14 in osteosarcoma remains undetermined. In the present study, we aimed to explore the expression pattern, biological function, and regulation of PTPN14 in osteosarcoma. Low PTPN14 expression levels were detected in osteosarcoma cells, and PTPN14 overexpression markedly decreased the proliferation, colony formation, and invasive potential of osteosarcoma cells. Bioinformatics analysis predicted PTPN14 as a potential target gene of microRNA-4295 (miR-4295), and this prediction was validated by a dual-luciferase reporter assay. PTPN14 expression was negatively modulated by miR-4295 in osteosarcoma cells. Moreover, PTPN14 expression was inversely correlated with miR-4295 expression in osteosarcoma tissues. Notably, miR-4295 inhibition significantly restricted the proliferation and invasion of osteosarcoma cells. PTPN14 overexpression or miR-4295 inhibition increased the phosphorylation of Yes-associated protein 1 (YAP1) and impeded YAP1 nuclear translocation, leading to inhibition of YAP1-mediated transcriptional activity. However, the miR-4925-inhibition-mediated antitumour effect was partially reversed by PTPN14 knockdown. Overall, these results demonstrate that PTPN14 is a miR-4295 target gene and it exerts a tumour-suppressive function in osteosarcoma cells via inactivation of YAP1. Our study uncovers a miR-4295-PTPN14-YAP1 signalling pathway that may play a crucial role in the progression of osteosarcoma.

Reduction in Cerebrospinal Fluid Volume as an Early Quantitative Biomarker of Cerebral Edema After Ischemic Stroke.

Background and Purpose- Cerebral edema (CED) develops in the hours to days after stroke; the resulting increase in brain volume may lead to midline shift (MLS) and neurological deterioration. The time course and implications of edema formation are not well characterized across the spectrum of stroke. We analyzed displacement of cerebrospinal fluid (ΔCSF) as a dynamic quantitative imaging biomarker of edema formation. Methods- We selected subjects enrolled in a stroke cohort study who presented within 6 hours of onset and had baseline and ≥1 follow-up brain computed tomography scans available. We applied a neural network-based algorithm to quantify hemispheric CSF volume at each imaging time point and modeled CSF trajectory over time (using a piecewise linear mixed-effects model). We evaluated ΔCSF within the first 24 hours as an early biomarker of CED (defined as developing MLS on computed tomography beyond 24 hours) and poor outcome (modified Rankin Scale score, 3-6). Results- We had serial imaging in 738 subjects with stroke, of whom 91 (13%) developed CED with MLS. Age did not differ (69 versus 70 years), but baseline National Institutes of Health Stroke Scale was higher (16 versus 7) and baseline CSF volume lower (132 versus 161 mL, both P<0.001) in those with CED. ΔCSF was faster in those developing MLS, with the majority seen by 24 hours (36% versus 11% or 2.4 versus 0.8 mL/h; P<0.0001). Risk of CED almost doubled for every 10% ΔCSF within 24 hours (odds ratio, 1.76 [95% CI, 1.46-2.14]), adjusting for age, glucose, and National Institutes of Health Stroke Scale. Risk of neurological deterioration (1.6-point increase in National Institutes of Health Stroke Scale at 24 hours) and poor outcome (adjusted odds ratio, 1.34 [95% CI, 1.15-1.56]) was also greater for every 10% increase in ΔCSF. Conclusions- CSF volumetrics provides quantitative evaluation of early edema formation. ΔCSF from baseline to 24-hour computed tomography is a promising early biomarker for the development of MLS and worse neurological outcome.

Quantitative receptor-based imaging of tumor proliferation with the sigma-2 ligand [(18)F]ISO-1.

The sigma-2 receptor is expressed in higher density in proliferating (P) tumor cells versus quiescent (Q) tumor cells, thus providing an attractive target for imaging the proliferative status (i.e., P:Q ratio) of solid tumors. Here we evaluate the utility of the sigma-2 receptor ligand 2-(2-[(18)F]fluoroethoxy)-N-(4-(3,4-dihydro-6,7-dimethoxyisoquinolin-2(1H)-yl)butyl)-5-methyl-benzamide, [(18)F]ISO-1, in two different rodent models of breast cancer. In the first study, small animal Positron Emission Tomography (PET) imaging studies were conducted with [(18)F]ISO-1 and (18)FDG in xenografts of mouse mammary tumor 66 and tracer uptake was correlated with the in vivo P:Q ratio determined by flow cytometric measures of BrdU-labeled tumor cells. The second model utilized a chemically-induced (N-methyl-N-nitrosourea [MNU]) model of rat mammary carcinoma to correlate measures of [(18)F]ISO-1 and FDG uptake with MR-based volumetric measures of tumor growth. In addition, [(18)F]ISO-1 and FDG were used to assess the response of MNU-induced tumors to bexarotene and Vorozole therapy. In the mouse mammary 66 tumors, a strong linear correlation was observed between the [(18)F]ISO-1 tumor: background ratio and the proliferative status (P:Q ratio) of the tumor (R = 0.87). Similarly, measures of [(18)F]ISO-1 uptake in MNU-induced tumors significantly correlated (R = 0.68, P<0.003) with changes in tumor volume between consecutive MR imaging sessions. Our data suggest that PET studies of [(18)F]ISO-1 provide a measure of both the proliferative status and tumor growth rate, which would be valuable in designing an appropriate treatment strategy.

Abnormal expression of early growth response 1 in gastric cancer: association with tumor invasion, metastasis and heparanase transcription.

Given that previous studies indicated that early growth response 1 (EGR1) exerts pro-tumorigenic effects through regulating heparanase (HPA) transcription, it was hypothesized that EGR1 may correlate with the progression of gastric cancer. One hundred and fifteen patients with gastric cancer were evaluated for the protein and transcript expression of EGR1 and HPA on immunohistochemistry and real-time quantitative polymerase chain reaction (PCR). In normal gastric mucosa, EGR1 protein expression was absent or weak, whereas gastric cancer was positive for EGR1. Seventy gastric cancer patients (60.9%) were positive for cytoplasmic EGR1 expression, and 26 (22.6%) had nuclear expression of EGR1. In the gastric cancer examined, the transcripts of EGR1 were enhanced compared to that of normal gastric mucosa, and positively correlated with EGR1 protein expression. The cytoplasmic or nuclear expression of EGR1 and its transcripts in gastric cancer was positively correlated with tumor infiltration (P < 0.05), lymph node and distant metastasis (P < 0.05), tumor node metastasis (TNM) stages (P < 0.05), but not with age, gender, tumor location and size, histological types or differentiation. Moreover, the protein and transcript expression of EGR1 was correlated with that of HPA in gastric cancer. These results indicate that aberrant expression of EGR1 in gastric cancer is associated with tumor invasion and metastasis, and HPA transcription.