Microvesicles as a Biomarker for Tumor Progression versus Treatment Effect in Radiation/Temozolomide-Treated Glioblastoma Patients

The standard of care for glioblastoma (GB) is surgery followed by concurrent radiation therapy (RT) and temozolomide (TMZ) and then adjuvant TMZ. This regime is associated with increased survival but also increased occurrence of equivocal imaging findings, e.g., tumor progression (TP) versus treatment effect (TE), which is also referred to as pseudoprogression (PsP). Equivocal findings make decisions regarding further treatment difficult and often delayed. Because none of the current imaging assays have proven sensitive and specific for differentiation of TP versus TE/PsP, we investigated whether blood-derived microvesicles (MVs) would be a relevant assay. METHODS: 2.8 ml of citrated blood was collected from patients with GB at the time of their RT simulation, at the end of chemoradiation therapy (CRT), and multiple times following treatment. MVs were collected following multiple centrifugations (300g, 2500g, and 15,000g). The pellet from the final spin was analyzed using flow cytometry. A diameter of approximately 300 nm or greater and Pacific Blue–labeled Annexin V positivity were used to identify the MVs reported herein. RESULTS: We analyzed 19 blood samples from 11 patients with GB. MV counts in the patients with stable disease or TE/PsP were significantly lower than patients who developed TP (P = .014). CONCLUSION: These preliminary data suggest that blood analysis for MVs from GB patients receiving CRT may be useful to distinguish TE/PsP from TP. MVs may add clarity to standard imaging for decision making in patients with equivocal imaging findings.     

Assessment of Treatment Response by Total Tumor Volume and Global Apparent Diffusion Coefficient Using Diffusion-Weighted MRI in Patients with Metastatic Bone Disease: A Feasibility Study

We describe our semi-automatic segmentation of whole-body diffusion-weighted MRI (WBDWI) using a Markov random field (MRF) model to derive tumor total diffusion volume (tDV) and associated global apparent diffusion coefficient (gADC); and demonstrate the feasibility of using these indices for assessing tumor burden and response to treatment in patients with bone metastases.WBDWI was performed on eleven patients diagnosed with bone metastases from breast and prostate cancers before and after anti-cancer therapies. Semi-automatic segmentation incorporating a MRF model was performed in all patients below the C4 vertebra by an experienced radiologist with over eight years of clinical experience in body DWI. Changes in tDV and gADC distributions were compared with overall response determined by all imaging, tumor markers and clinical findings at serial follow up. The segmentation technique was possible in all patients although erroneous volumes of interest were generated in one patient because of poor fat suppression in the pelvis, requiring manual correction. Responding patients showed a larger increase in gADC (median change = +0.18, range = −0.07 to +0.78×10⁻³ mm²/s) after treatment compared to non-responding patients (median change = −0.02, range = −0.10 to +0.05×10⁻³ mm²/s, p = 0.05, Mann-Whitney test), whereas non-responding patients showed a significantly larger increase in tDV (median change = +26%, range = +3 to +284%) compared to responding patients (median change = −50%, range = −85 to +27%, p = 0.02, Mann-Whitney test). Semi-automatic segmentation of WBDWI is feasible for metastatic bone disease in this pilot cohort of 11 patients, and could be used to quantify tumor total diffusion volume and median global ADC for assessing response to treatment.     

Secreted Gaussia Luciferase as a Biomarker for Monitoring Tumor Progression and Treatment Response of Systemic Metastases

Background

Currently, only few techniques are available for quantifying systemic metastases in preclinical model. Thus techniques that can sensitively detect metastatic colonization and assess treatment response in real-time are urgently needed. To this end, we engineered tumor cells to express a naturally secreted Gaussia luciferase (Gluc), and investigated its use as a circulating biomarker for monitoring viable metastatic or primary tumor growth and their treatment responses.

Methodology/Principal Findings

We first developed orthotopic primary and metastatic breast tumors with derivative of MDA-MB-231 cells expressing Gluc. We then correlated tumor burden with Gluc activity in the blood and urine along with bioluminescent imaging (BLI). Second, we utilized blood Gluc assay to monitor treatment response to lapatinib in an experimental model of systemic metastasis. We observed good correlation between the primary tumor volume and Gluc concentration in blood (R² = 0.84) and urine (R² = 0.55) in the breast tumor model. The correlation deviated as a primary tumor grew due to a reduction in viable tumor fraction. This was also supported by our mathematical models for tumor growth to compare the total and viable tumor burden in our model. In the experimental metastasis model, we found numerous brain metastases as well as systemic metastases including bone and lungs. Importantly, blood Gluc assay revealed early growth of metastatic tumors before BLI could visualize their presence. Using secreted Gluc, we localized systemic metastases by BLI and quantitatively monitored the total viable metastatic tumor burden by blood Gluc assay during the course of treatment with lapatinib, a dual tyrosine kinase inhibitor of EGFR and HER2.

Conclusion/Significance

We demonstrated secreted Gluc assay accurately reflects the amount of viable cancer cells in primary and metastatic tumors. Blood Gluc activity not only tracks metastatic tumor progression but also serves as a longitudinal biomarker for tumor response to treatments.     

Glioma: Application of Whole-Tumor Texture Analysis of Diffusion-Weighted Imaging for the Evaluation of Tumor Heterogeneity

Background and Purpose

To apply a texture analysis of apparent diffusion coefficient (ADC) maps to evaluate glioma heterogeneity, which was correlated with tumor grade.

Materials and Methods

Forty patients with glioma (WHO grade II (n = 8), grade III (n = 10) and grade IV (n = 22)) underwent diffusion-weighted imaging (DWI), and the corresponding ADC maps were obtained. Regions of interest containing the lesions were drawn on every section of the ADC map containing the tumor, and volume-based data of the entire tumor were constructed. Texture and first order features including entropy, skewness and kurtosis were derived from the ADC map using in-house software. A histogram analysis of the ADC map was also performed. The texture and histogram parameters were compared between low-grade and high-grade gliomas using an unpaired student’s t-test. Additionally, a one-way analysis of variance analysis with a post-hoc test was performed to compare the parameters of each grade.

Results

Entropy was observed to be significantly higher in high-grade gliomas than low-grade tumors (6.861±0.539 vs. 6.261±0.412, P  = 0.006). The fifth percentiles of the ADC cumulative histogram also showed a significant difference between high and low grade gliomas (836±235 vs. 1030±185, P = 0.037). Only entropy proved to be significantly different between grades III and IV (6.295±0.4963 vs. 7.119±0.3165, P<0.001). The diagnostic accuracy of ADC entropy was significantly higher than that of the fifth percentile of the ADC histogram (P = 0.0034) in distinguishing high- from low-grade glioma.

Conclusion

A texture analysis of the ADC map based on the entire tumor volume can be useful for evaluating glioma grade, which provides tumor heterogeneity.     

TIP-1 Translocation onto the Cell Plasma Membrane Is a Molecular Biomarker of Tumor Response to Ionizing Radiation

Background

Tumor response to treatment has been generally assessed with anatomic and functional imaging. Recent development of in vivo molecular and cellular imaging showed promise in time-efficient assessment of the therapeutic efficacy of a prescribed regimen. Currently, the in vivo molecular imaging is limited with shortage of biomarkers and probes with sound biological relevance. We have previously shown in tumor-bearing mice that a hexapeptide (HVGGSSV) demonstrated potentials as a molecular imaging probe to distinguish the tumors responding to ionizing radiation (IR) and/or tyrosine kinase inhibitor treatment from those of non-responding tumors.

Methodology/Principal Findings

In this study we have studied biological basis of the HVGGSSV peptide binding within the irradiated tumors by use of tumor-bearing mice and cultured cancer cells. The results indicated that Tax interacting protein 1 (TIP-1, also known as Tax1BP3) is a molecular target that enables the selective binding of the HVGGSSV peptide within irradiated xenograft tumors. Optical imaging and immunohistochemical staining indicated that a TIP-1 specific antibody demonstrated similar biodistribution as the peptide in tumor-bearing mice. The TIP-1 antibody blocked the peptide from binding within irradiated tumors. Studies on both of human and mouse lung cancer cells showed that the intracellular TIP-1 relocated to the plasma membrane surface within the first few hours after exposure to IR and before the onset of treatment associated apoptosis and cell death. TIP-1 relocation onto the cell surface is associated with the reduced proliferation and the enhanced susceptibility to the subsequent IR treatment.

Conclusions/Significance

This study by use of tumor-bearing mice and cultured cancer cells suggested that imaging of the radiation-inducible TIP-1 translocation onto the cancer cell surface may predict the tumor responsiveness to radiation in a time-efficient manner and thus tailor radiotherapy of cancer.     

Histogram Analysis Parameters Apparent Diffusion Coefficient for Distinguishing High and Low-Grade Meningiomas: A Multicenter Study

Low grade meningiomas have better prognosis than high grade meningiomas. The aim of this study was to measure apparent diffusion coefficient (ADC) histogram analysis parameters in different meningiomas in a large multicenter sample and to analyze the possibility of several parameters for predicting tumor grade and proliferation potential. Overall, 148 meningiomas from 7 institutions were evaluated in this retrospective study. Grade 1 lesions were diagnosed in 101 (68.2%) cases, grade 2 in 41 (27.7%) patients, and grade 3 in 6 (4.1%) patients. All tumors were investigated by MRI (1.5 T scanner) by using diffusion weighted imaging (b values of 0 and 1000 s/mm²). For every lesion, the following parameters were calculated: mean ADC, maximum ADC, minimum ADC, median ADC, mode ADC, ADC percentiles P10, P25, P75, P90, kurtosis, skewness, and entropy. The comparison of ADC values was performed by Mann–Whitney-U test. Correlation between different ADC parameters and KI 67 was calculated by Spearman's rank correlation coefficient. Grade 2/3 meningiomas showed statistically significant lower ADC histogram analysis parameters in comparison to grade 1 tumors, especially ADC median. A threshold value of 0.82 for ADC median to predict tumor grade was estimated (sensitivity?=?82.2%, specificity?=?63.8%, accuracy?=?76.4%, positive and negative predictive values were 83% and 62.5%, respectively).All ADC parameters except maximum ADC showed weak significant correlations with KI 67, especially ADC P25 (P?=??.340, P?=?.0001).     

Magnetic Resonance Imaging (MRI) of Intratumoral Voxel Heterogeneity as a Potential Response Biomarker: Assessment in a HER2+ Esophageal Adenocarcinoma Xenograft Following Trastuzumab and/or Cisplatin Therapy

We evaluated magnetic resonance imaging (MRI) voxel heterogeneity following trastuzumab and/or cisplatin in a HER2+ esophageal xenograft (OE19) as a potential response biomarker. OE19 xenografts treated with saline (controls), monotherapy, or combined cisplatin and trastuzumab underwent 9.4-T MRI. Tumor MRI parametric maps of T1 relaxation time (pre/post contrast), T2 relaxation time, T2* relaxation rate (R2*), and apparent diffusion coefficient obtained before (TIME0), after 24 hours (TIME1), and after 2 weeks of treatment (TIME2) were analyzed. Voxel histogram and fractal parameters (from the whole tumor, rim and center, and as a ratio of rim‐to‐center) were derived. Tumors were stained for immunohistochemical markers of hypoxia (CA-IX), angiogenesis (CD34), and proliferation (Ki-67). Combination therapy reduced xenograft growth rate (relative change, ? +0.58 ± 0.43 versus controls, ? +4.1 ± 1.0; P = 0.008). More spatially homogeneous voxel distribution between the rim to center was noted after treatment for combination therapy versus controls, respectively, for contrast-enhanced T1 relaxation time (90th percentile: ratio 1.00 versus 0.88, P = 0.009), T2 relaxation time (mean: 1.00 versus 0.92, P = 0.006; median: 0.98 versus 0.91, P = 0.006; 75th percentile: 1.02 versus 0.94, P = 0.007), and R2* (10th percentile: 0.99 versus 1.26, P = 0.003). We found that combination and trastuzumab monotherapy reduced MRI spatial heterogeneity and growth rate compared to the control or cisplatin groups, the former providing adjunctive tumor response information.     

A Feasibility Study of Parametric Response Map Analysis of Diffusion-Weighted Magnetic Resonance Imaging Scans of Head and Neck Cancer Patients for Providing Early Detection of Therapeutic Efficacy

The parametric response map (PRM) was evaluated as an early surrogate biomarker for monitoring treatment-induced tissue alterations in patients with head and neck squamous cell carcinoma (HNSCC). Diffusion-weighted magnetic resonance imaging (DW-MRI) was performed on 15 patients with HNSCC at baseline and 3 weeks after treatment initiation of a nonsurgical organ preservation therapy (NSOPT) using concurrent radiation and chemotherapy. PRM was applied on serial apparent diffusion coefficient (ADC) maps that were spatially aligned using a deformable image registration algorithm to measure the tumor volume exhibiting significant changes in ADC (PRM_ADC). Pretherapy and midtherapy ADC maps, quantified from the DWIs, were analyzed by monitoring the percent change in whole-tumor mean ADC and the PRM metric. The prognostic values of percentage change in tumor volume and mean ADC and PRM_ADC as a treatment response biomarker were assessed by correlating with tumor control at 6 months. Pixel-wise differences as part of PRM_ADC analysis revealed regions where water mobility increased. Analysis of the tumor ADC histograms also showed increases in mean ADC as early as 3 weeks into therapy in patients with a favorable outcome. Nevertheless, the percentage change in mean ADC was found to not correlate with tumor control at 6 months. In contrast, significant differences in PRM_ADC and percentage change in tumor volume were observed between patients with pathologically different outcomes. Observations from this study have found that diffusion MRI, when assessed by PRM_ADC, has the potential to provide both prognostic and spatial information during NSOPT of head and neck cancer.     

Circulating Tumor Cells: Application as a Biomarker for Molecular Characterization and Predictor of Survival in an All-Comer Solid Tumor Phase I Clinical Study

Purpose

Clinical development of cancer drugs has a low success rate. Prognostic and predictive biomarkers using minimally invasive approaches hold promise for increasing the probability of success by enabling disease characterization, patient selection and early detection of drug treatment effect. Enumeration and molecular characterization of circulating tumor cells (CTC) may address some of these needs, and thus were evaluated for utility in a Phase I solid tumor clinical study.

Experimental Design

Blood samples for CTC analysis were obtained from 24 cancer patients in a multi-center all-comer Phase I study of MEDI-575, a novel anti-PDGFRα antibody. Samples were taken at screening and analyzed for enumeration of CTC using the CellSearch^® platform and for molecular characterization using a novel quantitative RT-PCR assay.

Results

Fifty-nine percent of the patients showed at least 1 CTC per 7.5 ml of blood at baseline. Progression-free survival (PFS) and overall survival (OS) of patients with 0 CTCs at baseline were longer than PFS and Os for patients with 1-3 and >3 CTCs (8.8 versus 1.4 and 1.3 months PFS, P = 0.02; 9.0 vs 7.4 and 3.5 months OS, P = 0.20, respectively). Patients with 0 CTC showed a greater percentage of stable disease than the other 2 groups with 1-3 and >3 CTCs (57% vs 29% and 0%). The multimarker qRT-PCR method detected CTC in 40% of the patients, and 80% of these patients were positive for pre-selected drug target genes.

Conclusion

CTC enumeration of patients in an all-comer study is feasible and may allow for patient stratification for PFS and Os to evaluate the clinical response of investigational agents. Gene expression profiling of isolated CTC may provide a means for molecular characterization of selected tumor targets.     

Diffusion Magnetic Resonance Imaging: An Imaging Treatment Response Biomarker to Chemoradiotherapy in a Mouse Model of Squamous Cell Cancer of the Head and Neck

For the treatment of squamous cell cancer of the head and neck (SCCHN), the assessment of treatment response is traditionally accomplished by volumetric measurements and has been suggested to be prognostic for an eventual response to treatment. An early evaluation response during the course of radiation therapy could provide an opportunity to tailor treatment to individual patients. Diffusion magnetic resonance imaging (MRI) allows for the quantification of tissue water diffusion values, thus treatment-induced loss of tumor cells will result in the increase in water mobility at the microscopic level, which can be detected as an increase in tumor diffusion values before any volumetric changes occur. We evaluated the use of diffusion MRI as an imaging biomarker of treatment response in an orthotopic mouse model of SCCHN. Mice with murine squamous cells expressing the yeast transgene cytosine deaminase were treated with 5-fluorocytosine (5FC), ionizing radiation, and combined therapy and were compared with control animals both during and after treatment for changes in tumor volumes, diffusion values, and survival. Radiation therapy had minimal effect on volumetric growth rate, diffusion, or survival. Although 5FC and combination treatment resulted in similar reductions in tumor volumes, the combination treatment elicited a much greater increase in tumor diffusion values, which correlated with improved survival. Thus, diffusion MRI as an imaging biomarker has a potential for early evaluation of the response to chemoradiation treatment in SCCHN.     

Real-Time Measurement of Functional Tumor Volume by MRI to Assess Treatment Response in Breast Cancer Neoadjuvant Clinical Trials: Validation of the Aegis SER Software Platform

PURPOSE: To evaluate the Aegis software implementation for real-time calculation of functional tumor volume (FTV) in the neoadjuvant breast cancer treatment trial setting. METHODS: The validation data set consisted of 689 contrast-enhanced magnetic resonance imaging (MRI) examinations from the multicenter American College of Radiology Imaging Network 6657 study. Subjects had stage III tumors ≥3 cm in diameter and underwent MRI before, during, after receiving anthracycline-cyclophosphamide chemotherapy. Studies were previously analyzed by the University of California San Francisco core laboratory using the three-timepoint signal enhancement ratio (SER) FTV algorithm; FTV measurement was subsequently implemented on the Hologic (formerly Sentinelle Medical Inc) Aegis platform. All cases were processed using predefined volumes of interest with no user interaction. Spearman rank correlation was evaluated for all study sites and visits. Cox proportional hazards analysis was used to compare predictive performance of the platforms for recurrence-free survival (RFS) time. RESULTS: Overall agreement between platforms was good; ρ varied from 0.96 to 0.98 for different study visits. Site-by-site analysis showed considerable variation, from ρ = 0.54 to near perfect agreement (ρ = 1.000) for several sites. Mean absolute difference between platforms ranged from 1.67 cm³ pretreatment to 0.2 cm³ posttreatment. The two platforms showed essentially identical performance for predicting RFS using pretreatment or posttreatment FTV. CONCLUSION: Implementation of the SER FTV algorithm on a commercial platform for real-time MRI volume assessments showed very good agreement with the reference core laboratory system, but variations by site and outlier analysis point out sensitivities to implementation-specific differences.     

Noninvasive Assessment of Tumor VEGF Receptors in Response to Treatment with Pazopanib: A Molecular Imaging Study

Vascular endothelial growth factor (VEGF) and its receptors (VEGFRs) drive angiogenesis, and several VEGFR inhibitors are already approved for use as single agents or in combination with chemotherapy. Although there is a clear benefit with these drugs in a variety of tumors, the clinical response varies markedly among individuals. Therefore, there is a need for an efficient method to identify patients who are likely to respond to antiangiogenic therapy and to monitor its effects over time. We have recently developed a molecular imaging tracer for imaging VEGFRs known as scVEGF/^99mTc; an engineered single-chain (sc) form of VEGF radiolabeled with technetium Tc 99m (^99mTc). After intravenous injection, scVEGF/^99mTc preferentially binds to and is internalized by VEGFRs expressed within tumor vasculature, providing information on prevalence of functionally active receptors. We now report that VEGFR imaging readily detects the effects of pazopanib, a small-molecule tyrosine kinase inhibitor under clinical development, which selectively targets VEGFR, PDGFR, and c-Kit in mice with HT29 tumor xenografts. Immunohistochemical analysis confirmed that the changes in VEGFR imaging reflect a dramatic pazopanib-induced decrease in the number of VEGFR-2⁺/CD31⁺ endothelial cells (ECs) within the tumor vasculature followed by a relative increase in the number of ECs at the tumor edges. We suggest that VEGFR imaging can be used for the identification of patients that are responding to VEGFR-targeted therapies and for guidance in rational design, dosing, and schedules for combination regimens of antiangiogenic treatment.     

Serum Myeloperoxidase as a Biomarker of Asthma Severity Among Adults: A Case Control Study

Background:The contribution of neutrophils is still indistinct in the inflammatory response of bronchial asthma (BAs). Myeloperoxidase (MPO) is an enzyme released from the primary azurophilic granules of the neutrophils. The study aimed to evaluate the levels of serum MPO as a biomarker for the assessment of the level of asthma control. Methods:The study participants included 94 asthmatic patients and 86 healthy controls. The identification of asthma severity had assessed using the ''''Global Initiative for Asthma guidelines''''. Asthmatic adults had divided into three groups: Good (n= 22), partial (n= 30), and poor control (n= 44). Also, patients have been divided again into two groups (treated and untreated) for BAs.Results:The predicted FEV1% and the peak expiratory flow (PEF/L) of all participants had verified by spirometry. The mean patients’ age was 31.9±15.1 year, with a predominance of females. The mean asthma duration was 10.5±8.6 years. Mean spirometric parameters (FEV1 and PEF) were significantly lower among the patients (0.00). Significant higher MPO levels had observed among BAs patients (p-0.00). The MPO levels have not differed significantly with asthma levels and had significant differences with the history of treatment. There was a nonsignificant negative correlation between the mean MPO levels and the spirometry variables among the patients. ROC curves revealed a sensitivity, specificity, accuracy for MPO (80.9%, 72.1%, and 84.3%), respectively to predict asthmatic severity.Conclusion:There were significantly higher MPO levels compared to healthy controls. Levels of serum MPO had a non-significant positive correlation with levels of asthma control, but a negative non-significant correlation with spirometric results. Key Words: Asthma, And Neutrophils, FEV1, MPO, PEF     

A Model of Functional Brain Connectivity and Background Noise as a Biomarker for Cognitive Phenotypes: Application to Autism

We present an efficient approach to discriminate between typical and atypical brains from macroscopic neural dynamics recorded as magnetoencephalograms (MEG). Our approach is based on the fact that spontaneous brain activity can be accurately described with stochastic dynamics, as a multivariate Ornstein-Uhlenbeck process (mOUP). By fitting the data to a mOUP we obtain: 1) the functional connectivity matrix, corresponding to the drift operator, and 2) the traces of background stochastic activity (noise) driving the brain. We applied this method to investigate functional connectivity and background noise in juvenile patients (n = 9) with Asperger’s syndrome, a form of autism spectrum disorder (ASD), and compared them to age-matched juvenile control subjects (n = 10). Our analysis reveals significant alterations in both functional brain connectivity and background noise in ASD patients. The dominant connectivity change in ASD relative to control shows enhanced functional excitation from occipital to frontal areas along a parasagittal axis. Background noise in ASD patients is spatially correlated over wide areas, as opposed to control, where areas driven by correlated noise form smaller patches. An analysis of the spatial complexity reveals that it is significantly lower in ASD subjects. Although the detailed physiological mechanisms underlying these alterations cannot be determined from macroscopic brain recordings, we speculate that enhanced occipital-frontal excitation may result from changes in white matter density in ASD, as suggested in previous studies. We also venture that long-range spatial correlations in the background noise may result from less specificity (or more promiscuity) of thalamo-cortical projections. All the calculations involved in our analysis are highly efficient and outperform other algorithms to discriminate typical and atypical brains with a comparable level of accuracy. Altogether our results demonstrate a promising potential of our approach as an efficient biomarker for altered brain dynamics associated with a cognitive phenotype.     

The Neural Correlates of Shoulder Apprehension: A Functional MRI Study

Although shoulder apprehension is an established clinical finding and is important for the prevention of shoulder dislocation, how this subjective perception is evoked remains unclear. We elucidated the functional neuroplasticity associated with apprehension in patients with recurrent anterior shoulder instability (RSI) using functional magnetic resonance imaging (fMRI). Twelve healthy volunteers and 14 patients with right-sided RSI performed a motor imagery task and a passive shoulder motion task. Brain activity was compared between healthy participants and those with RSI and was correlated with the apprehension intensity reported by participants after each task. Compared to healthy volunteers, participants with RSI exhibited decreased brain activity in the motor network, but increased activity in the hippocampus and amygdala. During the passive motion task, participants with RSI exhibited decreased activity in the left premotor and primary motor/somatosensory areas. Furthermore, brain activity was correlated with apprehension intensity in the left amygdala and left thalamus during the motor imagery task (memory-induced), while a correlation between apprehension intensity and brain activity was found in the left prefrontal cortex during the passive motion task (instability-induced). Our findings provide insight into the pathophysiology of RSI by identifying its associated neural alterations. We elucidated that shoulder apprehension was induced by two different factors, namely instability and memory.     

Cell Surface Profiling Using High-Throughput Flow Cytometry: A Platform for Biomarker Discovery and Analysis of Cellular Heterogeneity

Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.     

Relationship between G1287A of the NET Gene Polymorphisms and Brain Volume in Major Depressive Disorder: A Voxel-Based MRI Study

Background

Earlier studies implicated norepinephrine transporter (NET) gene (SLC6A2) polymorphisms in the etiology of major depressive disorder (MDD). Recently, two single nucleotide SLC6A2 polymorphisms, G1287A in exon 9 and T-182C in the promoter region, were found to be associated with MDD in different populations. We investigated the relationship between the brain volume and these two polymorphisms of the SLC6A2 in MDD patients.

Methods

We obtained 3D high-resolution T1-weighted images of 30 first-episode MDD patients and 48 age- and sex-matched healthy subjects (HS). All were divided into 4 groups based on polymorphism of either the G1287A or the T-182C genotype. VBM analysis examined the effects of diagnosis, genotype, and genotype-diagnosis interactions.

Results

Diagnosis effects on the brain morphology were found in the left superior temporal cortex. No significant genotype effects were found in the T-182C and the G1287A. A significant genotype (G1287A)–diagnosis interaction was found in the left dorsolateral prefrontal cortex. No significant genotype (T-182C)–diagnosis interaction effects were observed in any brain region.

Conclusions

In MDD patients there seems to be a relationship between the volume of the dorsolateral prefrontal cortex and polymorphism of the SLC6A2 G1287A gene.