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PDF file, 53K.

PDF file, 178K, Classification by cell-of-origin is associated with survival in univariate analyses.

Purpose: Better understanding of the underlying biology of primary central nervous system lymphomas (PCNSL) is critical for the development of early detection strategies, molecular markers, and new therapeutics. This study aimed to define genes associated with survival of patients with PCNSL.Experimental Design: Expression profiling was conducted on 32 PCNSLs. A gene classifier was developed using the random survival forests model. On the basis of this, prognosis prediction score (PPS) using immunohistochemical analysis is also developed and validated in another data set with 43 PCNSLs.Results: We identified 23 genes in which expressions were strongly and consistently related to patient survival. A PPS was developed for overall survival (OS) using a univariate Cox model. Survival analyses using the selected 23-gene classifiers revealed a prognostic value for high-dose methotrexate (HD-MTX) and HD-MTX–containing polychemotherapy regimen–treated patients. Patients predicted to have good outcomes by the PPS showed significantly longer survival than those with poor predicted outcomes (P < 0.0001). PPS using immunohistochemical analysis is also significant in test (P = 0.0004) and validation data set (P = 0.0281). The gene-based predictor was an independent prognostic factor in a multivariate model that included clinical risk stratification (P < 0.0001). Among the genes, BRCA1 protein expressions were most strongly associated with patient survival.Conclusion: We have identified gene expression signatures that can accurately predict survival in patients with PCNSL. These predictive genes should be useful as molecular biomarkers and they could provide novel targets for therapeutic interventions. Clin Cancer Res; 18(20); 5672–81. ©2012 AACR.

PDF file, 116K, Marginal plots for the six genes.

PDF file, 39K, QPCR data.

Primary central nervous system lymphoma (PCNSL) is a brain malignant non-Hodgkin’s B-cell lymphoma. The standard treatments are high-dose methotrexate (MTX)-based chemotherapies and deferred whole brain radiotherapy. However, MTX resistance-dependent global expression and signaling pathway changes and their relationship with prognoses have not yet been elucidated. Here, we conducted a global expression analysis with next-generation sequencing and gene set enrichment analysis (GSEA) in MTX-resistant PCNSL cell lines (HKBML-MTX and TK-MTX) and PCNSL tissues. In rank scores, genes listed in HKBML-MTX and TK-MTX were enriched in PCNSL with poor prognoses. In fold changes, a part of differentially-expressed genes in PCNSL tissues were also detected in HKBML-MTX and TK-MTX cells; FOXD2-AS1 and MMP19 were commonly expressed in both HKBML-MTX and TK-MTX, FABP5 and CD70 were HKBML-MTX-specifically expressed, and CLCN2, HOXB9, INE1, and LRP5L were TK-MTX-specifically expressed, which may provide a combination of prognostic markers on MTX-sensitivities in PCNSL. Additionally, PCNSL subgroups, divided with hierarchical clustering and Kaplan-Meier methods, included twenty commonly expressed genes in both HKBML-MTX and TK-MTX, ten HKBML-MTX-specifically expressed genes, and two TK-MTX-specifically expressed genes. These results suggest that the GSEA-assisted gene signatures can provide a combination for prognostic markers in recurrent PCNSL with MTX resistances.

This paper examines algorithms for estimating terrestrial albedo from the products of the Global Change Observation Mission – Climate (GCOM-C)/Second-generation Global Imager (SGLI), which was launched in December 2017 by the Japan Aerospace Exploration Agency. We selected two algorithms: one based on a bidirectional reflectance distribution function (BRDF) model and one based on multi-regression models. The former determines kernel-driven BRDF model parameters from multiple sets of reflectance and estimates the land surface albedo from those parameters. The latter estimates the land surface albedo from a single set of reflectance with multi-regression models. The multi-regression models are derived for an arbitrary geometry from datasets of simulated albedo and multi-angular reflectance. In experiments using in situ multi-temporal data for barren land, deciduous broadleaf forests, and paddy fields, the albedos estimated by the BRDF-based and multi-regression-based algorithms achieve reasonable root-mean-square errors. However, the latter algorithm requires information about the land cover of the pixel of interest, and the variance of its estimated albedo is sensitive to the observation geometry. We therefore conclude that the BRDF-based algorithm is more robust and can be applied to SGLI operational albedo products for various applications, including climate-change research., XXIV ISPRS Congress “Imaging today, foreseeing tomorrow, ” Commission III, 2021 edition, 5–9 July 2021

Exome-sequencing for somatic mutation detection and copy number variation analysis are effective and valid methods for evaluating human cancers in current molecular medicine. We conducted target amplicon exome-sequencing analyses using PCR target enrichment and next-generation sequencing on Ion Proton semiconductor sequencers. Twenty-seven primary central nervous system lymphoma (PCNSL) specimens and their corresponding noncancerous tissues were used for multiplex PCR amplification to obtain targeted coverages of the entire coding regions of 409 cancer-related genes. The average of the total numbers of somatic mutations including single-nucleotide variations and insertion/deletion mutations in each specimen was 13.3. Of these, the average of the ratios of nonsynonymous substitutions in each specimen was 74.8%. The most frequent mutations in 27 specimens were in PIM1, MYD88, CD79B, DST, IRF4, ERBB3, MYH11, DCC, and KMT2D. Furthermore, somatic mutations of MYH11 were related to poor prognoses in PCNSL patients. Copy number variations were also duplicated and/or deleted from deep-sequencing in segmental genomic islands. In addition to these prognostic marker candidates, analysis of RTK-RAS-MAPK signaling and the PTEN-PI3K-AKT proapoptotic pathway showed that somatic activations and aberrations, respectively, may be involved in a promising central oncopathway harboring mTOR, c-Myc, FOXO1, and p53. This study provides a foundation for molecular targeted therapies based on genome diagnostics and prognosis in PCNSL.

We constructed a bi-directional reflectance distribution function (BRDF) observation system on a 25-m-high tower surrounded by mature larch forests at the foot of Mt. Yatsugatake, central Japan. The BRDF feature (strong/weak reflections in a backward/forward scattering areas) is related closely to the 3D structure and biophysical parameters of forests. However, because of the difficulty of observations, observational BRDF data of mature forests are scarce, except for those of Boreal Ecosystem –Atmosphere Study (BOREAS). We made BRDF observations 10 times during 2007 to ascertain BRDF characteristics in each season. For comparison to these BRDF data, a semi-empirical BRDF model (Ross–thick Li–sparse kernel model) was introduced. This model can reproduce the BRDF data fairly well under identical solar conditions in each season. Then, seasonal changes of the vegetation structure and possible relations with BRDF were discussed. They are summarized as follows: (1) The forest BRDF changes distinctly and seasonally depending on the phenology. (2) The forest BRDF is influenced primarily by clarity of the geometrical profile on the forest surface, which is affected by shadow. However, the forest BRDF might be influenced by other factors such as the physiological characteristics of leaves and slight change of vegetation structure such as forest floor conditions and leaf angles during summer. (3) Features of forest BRDF must therefore appear during summer when the crown shape is distinctive. Furthermore, BRDF features appear distinctly as seasons progress, e.g., by autumn leaves and defoliation, when the unevenness of forests increases. These findings can promote monitoring of vegetation using multi-angular satellite observations.

Japan Aerospace Exploration Agency (JAXA) had launched new Earth observation satellite GCOM-C in the end of 2017. The core sensor of GCOM-C, Second Generation Global Imager (SGLI) has a set of along track slant viewing Visible and Near Infrared Radiometer (VNR). These multi-angular views aim to detect the structural information from vegetation canopy, especially forest canopy, for estimating productivity of the vegetation. SGLI Land science team has been developing the algorithm for Above Ground Biomass, Vegetation Index, Shadow Index, etc.We developed the ground observation method using Unmanned Aerial Vehicle (UAV) in order to contribute the algorithm development and its validation. Mainly, multi-angular spectral observation method and simple BRF model have been developed for estimating slant view response of forest canopy. The BRDF model developed by using multi-angular measurement has been able to obtain structural information from canopy. In addition, we have conducted some observation campaigns on typical forest in Japan in collaboration with other science team experienced with vegetation phenology and carbon flux measurement. Primary result, Above-ground biomass of these observations are also be demonstrated.

To validate terrestrial ecological products of the Global Change Observation Mission-Climate (GCOM-C) satellite, a large-scale ecological observation project "JAXA Super Sites 500" was initiated. The project’s purpose is to obtain the representative leaf area index (LAI), above-ground biomass (AGB), and fraction of absorbed PAR (fAPAR) in the satellite footprint scale. This study aimed to determine the appropriate observation methods in the satellite scale for the target land-cover types such as a deciduous broadleaved forest, evergreen/deciduous needle-leaved forests, and a grassland. As a result of the comparative observations, a combination method using litter-traps and LAI- 2200 was adopted as the LAI observation in a forest, a tree census method was adopted as the AGB observation in a forest, and a clipping method was adopted as the AGB and LAI observations in a grassland. LAI, AGB, and fAPAR were observed and were used to validate the GCOM-C terrestrial ecological products.

Background: GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic t...

MicroRNAs (miRNAs) are small RNA molecules that inhibit gene function by suppressing translation of target genes. However, in primary central nervous system lymphoma (PCNSL), the biological significance of miRNAs is largely unknown, although some miRNAs are known to be prognosis markers. Here, we analyzed 847 miRNAs expressed in 27 PCNSL specimens using microarray profiling and surveyed miRNA signature for prognostic prediction. Of these, 16 miRNAs were expressed in 27 PCNSL specimens at a frequency of 48%. Their variable importance measured by Random forest model revealed miR-192, miR-486, miR-28, miR-52, miR-181b, miR-194, miR-197, miR-93, miR-708, and let-7g as having positive effects; miR-29b-2*, miR-126, and miR-182 as having negative effects; and miR-18a*, miR-425, and miR-30d as neutral. After principal component analysis, the prediction formula for prognosis, consisting of the expression values of the above-mentioned miRNAs, clearly divided Kaplan-Meier survival curves by the calculated Z-score (HR = 6.4566, P = 0.0067). The 16 miRNAs were enriched by gene ontology terms including angiogenesis, cell migration and proliferation, and apoptosis, in addition to signaling pathways including TGF-β/SMAD, Notch, TNF, and MAPKinase. Their target genes included BCL2-related genes, HMGA2 oncogene, and LIN28B cancer stem cell marker. Furthermore, three miRNAs including miR-181b, miR-30d, and miR-93, selected from the 16 miRNAs, also showed comparable results for survival (HR = 8.9342, P = 0.0007), suggestive of a miRNA signature for prognostic prediction in PCNSL. These results indicate that this miRNA signature is useful for prognostic prediction in PCNSL and would help us understand target pathways for therapies in PCNSL.

Magnetic resonance imaging (MRI) is an important diagnostic tool for glioblastoma, with almost all cases showing characteristic imaging findings such as a heterogeneous-ring enhanced pattern associated with significant edema. However, MRI findings for early-stage glioblastoma are less clear. In this study, a retrospective review of MRI findings in five patients showed slight T2WI signal changes on initial scans that developed into typical imaging findings of a ring-like or heterogeneously enhanced bulky tumor within 6 months. The diagnoses based on initial MRI were low grade glioma in three cases, venous thrombosis in one case, and uncertain in one case. Four cases were treated with gross total resection, while one case underwent biopsy. Immunohistochemical examinations showed that two cases were p53-positive, and that all cases were IDH1 R132H-negative and had overexpression of EGFR. FISH analysis showed that all cases were 1p19q LOH-negative. De novo glioblastoma was the final diagnosis in all cases. Our results show that initial MRI findings in early-stage glioblastoma of small ill-defined T2WI hyperintense lesions with poor contrast develop to bulky mass lesions with typical findings for glioblastoma in as short a period as 2.5 months. The early MRI findings are difficult to distinguish from those for non-neoplastic conditions, including ischemic, degenerative or demyelinating processes. Thus, there is a need for proactive diagnosis of glioblastoma using short-interval MRI scans over several weeks, other imaging modalities, and biopsy or resection, particularly given the extremely poor prognosis of this disease.

BACKGROUND/AIM Programmed cell death ligand 1 (PD-L1)/programmed cell death 1 (PD-1) have been shown to predict response to PD-L1/PD-1-targeted therapy. We analyzed PD-L1 expression in primary central nervous system lymphomas (PCNSLs). MATERIALS AND METHODS PD-L1 protein and mRNA expression were evaluated in 64 PCNSL tissue samples. IFN-γ, IL-10, CD4, and CD8 mRNA expression was also evaluated. RESULTS PD-L1 protein was detected in tumor cells in 2 (4.1%) cases and in tumor microenvironments in 25 (52%) cases. PD-L1 mRNA positively correlated with IFN-γ (p=0.0024) and CD4 (p=0.0005) mRNA expression. IFN-γ mRNA positively correlated with CD8 mRNA expression (p=0.0001). Furthermore, tumor cell PD-L1 expression correlated positively with overall survival (p=0.0177), whereas microenvironmental PD-L1 expression exhibited an insignificant negative trend with overall survival (p=0.188). CONCLUSION PD-L1 was expressed on both tumor and/or tumor-infiltrating immune cells in PCNSL. The biological roles of this marker warrant further investigation.

We report long-term continuous phenological and sky images taken by time-lapse cameras through the Phenological Eyes Network ( http://www.pheno-eye.org . Accessed 29 May 2018) in various ecosystems from the Arctic to the tropics. Phenological images are useful in recording the year-to-year variability in the timing of flowering, leaf-flush, leaf-coloring, and leaf-fall and detecting the characteristics of phenological patterns and timing sensitivity among species and ecosystems. They can also help interpret variations in carbon, water, and heat cycling in terrestrial ecosystems, and be used to obtain ground-truth data for the validation of satellite-observed products. Sky images are useful in continuously recording atmospheric conditions and obtaining ground-truth data for the validation of cloud contamination and atmospheric noise present in satellite remote-sensing data. We have taken sky, forest canopy, forest floor, and shoot images of a range of tree species and landscapes, using time-lapse cameras installed on forest floors, towers, and rooftops. In total, 84 time-lapse cameras at 29 sites have taken 8 million images since 1999. Our images provide (1) long-term, continuous detailed records of plant phenology that are more quantitative than in situ visual phenological observations of index trees; (2) basic information to explain the responsiveness, vulnerability, and resilience of ecosystem canopies and their functions and services to changes in climate; and (3) ground-truthing for the validation of satellite remote-sensing observations.

Glioma stem cells (GSCs) may be a source of tumor progression and recurrence after multimodal therapy, because of their high invasive potential. The purpose of this study was to compare the invasive and migratory properties of GSCs and non-GSCs and examine the distribution of these cells in a mouse xenograft model. Three GSC lines, G144, Y02, and Y10, cultured from human glioblastoma, were used in the study. Matrigel-invasion assays of infiltration and time-lapse studies of migration were performed for comparison of the GSCs with the corresponding differentiated non-GSC lines. Cells were also transplanted into mouse brain and the different distribution of GSCs and non-GSCs was examined in the tumor xenograft model. All 3 GSC lines had greater invasion and migration ability than the corresponding non-GSCs. In vivo, GSCs infiltrated more widely than non-GSCs and reached the contralateral hemisphere via the corpus callosum in the early stage of tumorigenesis. GSCs also primarily penetrated the subventricular zone (SVZ). GSCs have high invasive potential and tend to be present in the outer tumor bulk and infiltrate the contralateral hemisphere via the corpus callosum, in addition to penetrating the SVZ.

Abnormal hemodynamics during extirpation of a para-medulla oblongata (MO) tumor is common and may be associated with direct vagal stimulation of the medullary circuit. However, resection of tumors on the dorsal MO may also induce hemodynamic instability without direct vagal stimulus. The objective of this study was to examine the characteristics of hemodynamic instability unrelated to vagal stimulus during dissection of an intra-fourth ventricular tumor with attachment to the dorsal MO. A retrospective analysis was performed in 13 patients. Abnormal hemodynamics were defined as a > 20% change from the means of the intraoperative mean arterial pressure (MAP) and heart rate (HR). Relationships of intraoperative hemodynamics were evaluated with various parameters, including the volume of the MO. Six patients (46.2%) had intraoperative hypertension during separation of the tumor bulk from the dorsal MO. The maximum MAP and HR in these patients were significantly greater than those in patients with normal hemodynamics (116.0 ± 18.0 mmHg versus 85.6 ± 6.5 mmHg; 124.3 ± 22.8 bpm versus 90.5 ± 14.7 bpm). All six cases with abnormal hemodynamics showed hemodynamic fluctuation during separation of the tumor bulk from the dorsal MO. The preoperative volume of the MO in these patients was 1.11 cc less than that in patients with normal hemodynamics, but the volume after tumor resection was similar in the two groups (5.23 cc and 5.12 cc). This suggests that the MO was compressed by the conglutinate tumor bulk, with resultant fluctuation of hemodynamics. Recognition of and preparation for this phenomenon are important for surgery on a tumor located on the dorsal MO.

OBJECTIVE To avoid ischemic complications, it is important to consider the arteries in resection planning for lesions such as a vascular intraparenchymal tumor and arteriovenous malformation. Here, the clinical application of laser speckle flow imaging (LSFI) as a complementary method for the management of mass lesion–related arteries during surgery was evaluated. METHODS LSFI was performed in 12 patients with mass lesion–related arteries and brain tumor or arteriovenous malformation. The portable LSFI device was centered over the surgical field, and the relative cerebral blood flow (CBF) before and after the temporary interruption of the arteries was measured through continuous recording. CBF fluctuations permitted the classification of 3 kinds of artery—a feeding artery (FA), a “passing through” artery (PA), and a combined FA and PA (FA+PA)—based on decreased relative CBF in the inner resection area and unchanged CBF in the surrounding area (FA), unchanged CBF in the inner area and decreased CBF in the surrounding area (PA), or decreased CBF in both areas (FA+PA). This information allowed the appropriate management of these arteries and avoidance of postoperative ischemic complications. RESULTS Good visualization of CBF in the surgical field and relative CBF measurements in the regions of interest were achieved in real time with excellent spatiotemporal resolution. In 11 patients (92%) and 20 regions of interest, a decline in CBF was observed after temporary interruption of the FA (n = 8), PA (n = 2), and FA+PA (n = 2) types. There was a significant average reduction in CBF of 15.3% ± 29.0%. There were no ischemic complications, and only 1 patient had a postoperative ischemic lesion caused by resection through an artery that could not be viewed by LSFI due to a positional problem. CONCLUSIONS LSFI permits noninvasive and rapid intraoperative real-time recognition of mass lesion–related vasculature. This information can be used to avoid ischemic complications as a procedure complementary to neurophysiological monitoring.

The canopy shadow fraction (CSF) is composed of the fractional area covered by shadowed tree crowns and shadowed backgrounds for a given illumination and view geometry. Since the CSF is related to the canopy biological and structural features, an accurate estimation of the CSF is expected for better understanding of the canopy characteristics. This study explores an algorithm for an automated extraction of the CSF using near-surface remote sensing method. The high-spatial resolution true-color images over different forested canopies were acquired using an unmanned helicopter. For each site, the images of the same target canopy from multiple view zenith angles (VZA) were taken at the principal plane. The digital images were processed to extract the CSF using the color vegetation indices (CVI) combined with an image threshold algorithm. The CSF was measured based on visual interpretation of the grayscale images. For an automated extraction of the CSF, different CVI related to CSF were assessed with Otsu threshold algorithm. A new CVI called the blue deficient index (BDI) was proposed as an indicator of the CSF exploiting the canopy spectral properties. The performance of each automated extraction method was evaluated with comparison to measured CSF. Among the methods assessed under the study, the CSF estimated by the BDI with the Otsu algorithm was found to be most closely related to the measured CSF. After a successful extraction of the CSF, the effect of VZA on CSF was analyzed. The substantial variation of the CSF with respect to the VZA in the principal plane was confirmed for a given solar position.

Purpose: Better understanding of the underlying biology of primary central nervous system lymphomas (PCNSL) is critical for the development of early detection strategies, molecular markers, and new therapeutics. This study aimed to define genes associated with survival of patients with PCNSL. Experimental Design: Expression profiling was conducted on 32 PCNSLs. A gene classifier was developed using the random survival forests model. On the basis of this, prognosis prediction score (PPS) using immunohistochemical analysis is also developed and validated in another data set with 43 PCNSLs. Results: We identified 23 genes in which expressions were strongly and consistently related to patient survival. A PPS was developed for overall survival (OS) using a univariate Cox model. Survival analyses using the selected 23-gene classifiers revealed a prognostic value for high-dose methotrexate (HD-MTX) and HD-MTX–containing polychemotherapy regimen–treated patients. Patients predicted to have good outcomes by the PPS showed significantly longer survival than those with poor predicted outcomes (P < 0.0001). PPS using immunohistochemical analysis is also significant in test (P = 0.0004) and validation data set (P = 0.0281). The gene-based predictor was an independent prognostic factor in a multivariate model that included clinical risk stratification (P < 0.0001). Among the genes, BRCA1 protein expressions were most strongly associated with patient survival. Conclusion: We have identified gene expression signatures that can accurately predict survival in patients with PCNSL. These predictive genes should be useful as molecular biomarkers and they could provide novel targets for therapeutic interventions. Clin Cancer Res; 18(20); 5672–81. ©2012 AACR.