Cerebrospinal Fluid MicroRNA Signatures as Diagnostic Biomarkers in Brain Tumors

Central nervous system (CNS) malignancies include primary tumors that originate within the CNS as well as secondary tumors that develop as a result of metastatic spread. Circulating microRNAs (miRNAs) were found in almost all human body fluids including cerebrospinal fluid (CSF), and they seem to be highly stable and resistant to even extreme conditions. The overall aim of our study was to identify specific CSF miRNA patterns that could differentiate among brain tumors. These new biomarkers could potentially aid borderline or uncertain imaging results onto diagnosis of CNS malignancies, avoiding most invasive procedures such as stereotactic biopsy or biopsy. In total, 175 brain tumor patients (glioblastomas, low-grade gliomas, meningiomas and brain metastases), and 40 non-tumor patients with hydrocephalus as controls were included in this prospective monocentric study. Firstly, we performed high-throughput miRNA profiling (Illumina small RNA sequencing) on a discovery cohort of 70 patients and 19 controls and identified specific miRNA signatures of all brain tumor types tested. Secondly, validation of 9 candidate miRNAs was carried out on an independent cohort of 105 brain tumor patients and 21 controls using qRT-PCR. Based on the successful results of validation and various combination patterns of only 5 miRNA levels (miR-30e, miR-140, let-7b, mR-10a and miR-21-3p) we proposed CSF-diagnostic scores for each tumor type which enabled to distinguish them from healthy donors and other tumor types tested. In addition to this primary diagnostic tool, we described the prognostic potential of the combination of miR-10b and miR-196b levels in CSF of glioblastoma patients. In conclusion, we performed the largest study so far focused on CSF miRNA profiling in patients with brain tumors, and we believe that this new class of biomarkers have a strong potential as a diagnostic and prognostic tool in these patients.

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Comparison between neuroimaging classifications and histopathological diagnoses using an international multicenter brain tumor magnetic resonance imaging database

Journal of Neurosurgery ◽

10.3171/jns.2006.105.1.6 ◽

2006 ◽

Vol 105 (1) ◽

pp. 6-14 ◽

Cited By ~ 39

Author(s):

Margarida Julià-Sapé ◽

Dionisio Acosta ◽

Carles Majós ◽

Àngel Moreno-Torres ◽

Pieter Wesseling ◽

...

Keyword(s):

Brain Tumor ◽

Magnetic Resonance ◽

Brain Tumors ◽

Mr Imaging ◽

High Specificity ◽

Low Grade ◽

Tumor Type ◽

Glial Tumor ◽

Predictive Values ◽

Tumor Types

Object The aim of this study was to estimate the accuracy of routine magnetic resonance (MR) imaging studies in the classification of brain tumors in terms of both cell type and grade of malignancy. Methods The authors retrospectively assessed the correlation between neuroimaging classifications and histopathological diagnoses by using multicenter database records from 393 patients with brain tumors. An ontology was devised to establish diagnostic agreement. Each tumor category was compared with the corresponding histopathological diagnoses by dichotomization. Sensitivity, specificity, positive and negative predictive values (PPVs and NPVs, respectively), and the Wilson 95% confidence intervals (CI) for each were calculated. In routine reporting of MR imaging examinations, tumor types and grades were classified with a high specificity (85.2–100%); sensitivity varied, depending on the tumor type and grade, alone or in combination. The recognition of broad diagnostic categories (neuroepithelial or meningeal lesions) was highly sensitive, whereas when both detailed type and grade were considered, sensitivity diverged, being highest in low-grade meningioma (sensitivity 100%, 95% CI 96.2–100.0%) and lowest in high-grade meningioma (sensitivity 0.0%, 95% CI 0.0–65.8%) and low-grade oligodendroglioma (sensitivity 15%, 95% CI 5.2–36.0%). In neuroepithelial tumors, sensitivity was inversely related to the precision in reporting of grade and cellular origin; “glioma” was a frequent neuroimaging classification associated with higher sensitivity in the corresponding category. The PPVs varied among categories, in general being greater than their prevalence in this dataset. The NPV was high in all categories (69.8–100%). Conclusions The PPVs and NPVs provided in this study may be used as estimates of posttest probabilities of diagnostic accuracy using MR imaging. This study targets the need for noninvasively increasing sensitivity in categorizing most brain tumor types while retaining high specificity, especially in the differentiation of high- and low-grade glial tumor classes.

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GENE-03. SPECIFIC SIGNATURES OF microRNA IN CEREBROSPINAL FLUID OF PATIENTS WITH PRIMARY BRAIN TUMORS AND METASTASES

Neuro-Oncology ◽

10.1093/neuonc/noz175.405 ◽

2019 ◽

Vol 21 (Supplement_6) ◽

pp. vi98-vi98

Author(s):

Radim Jancalek ◽

Martin Smrcka ◽

Alena Kopkova ◽

Jiri Sana ◽

Marek Vecera ◽

...

Keyword(s):

Cerebrospinal Fluid ◽

Czech Republic ◽

Brain Tumor ◽

Brain Tumors ◽

Brain Metastases ◽

Independent Set ◽

Low Grade ◽

Primary Brain Tumors ◽

Csf Analysis ◽

Different Levels

Abstract Cerebrospinal fluid (CSF) baths extracellular environment of the central nervous system, and thus, it is ideal source of tumor diagnostic biomarkers like microRNAs (miRNAs), short non-coding RNAs involved in the pathogenesis of many cancers. As dysregulated levels of brain tumor specific miRNAs have been already observed in CSF, analysis of CSF miRNAs in brain tumor patients might help to develop new diagnostic platform. Next-Generation sequencing (NGS) was performed for analysis of small RNAs in 89 CSF samples taken from 32 glioblastomas (GBM), 14 low-grade gliomas (LGG), 11 meningiomas, 13 brain metastases and 19 non-tumor donors. Subsequently, according to NGS results levels of 10 miRNAs were measured in independent set of CSF samples (41 GBM, 44 meningiomas, 12 brain metastases and 20 non-tumor donors) using TaqMan Advanced miRNA Assays. NGS analysis revealed 22, 12 and 35 CSF miRNAs with significantly different levels in GBM, meningiomas, and brain metastases (adj.p < 0.0005, adj.p < 0.01, and adj.p < 0.005) respectively, in comparison with non-tumor CSF samples. Subsequent validation of selected CSF miRNAs has confirmed different levels of 7 miRNAs in GBM, 2 in meningiomas, and 2 in brain metastases compared to non-tumors. Panel of miR-30e-5p and miR-140-5p was able to distinguish brain metastases with 65% sensitivity and 100% specificity compared to non-tumor samples (AUC = 0.8167); panel of miR-21-3p and miR-196-5p classified metastatic patients with 78% sensitivity and 92 % specificity in comparison to GBM (AUC = 0.90854) and with 75% sensitivity and 83% specificity compared to meningiomas (AUC = 0.84848). We have observed that CSFs from patients with various primary brain tumors and metastases are characterized by specific miRNA signatures. This work was supported by the Ministry of Health, Czech Republic grant nr. NV18-03-00398 and the Ministry of Education, Youth and Sports, Czech Republic under the project CEITEC 2020 (LQ1601).

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Potential biomarkers of childhood brain tumor identified by proteomics of cerebrospinal fluid from extraventricular drainage (EVD)

Scientific Reports ◽

10.1038/s41598-020-80647-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Maurizio Bruschi ◽

Andrea Petretto ◽

Armando Cama ◽

Marco Pavanello ◽

Martina Bartolucci ◽

...

Keyword(s):

Cerebrospinal Fluid ◽

Brain Tumor ◽

Brain Tumors ◽

Residual Disease ◽

S100 Protein ◽

Therapy Response ◽

Bioinformatic Analysis ◽

Low Grade ◽

Protein Biomarkers ◽

Bodily Fluids

AbstractBrain tumors are the most common solid tumors in childhood. There is the need for biomarkers of residual disease, therapy response and recurrence. Cerebrospinal fluid (CSF) is a source of brain tumor biomarkers. We analyzed the proteome of waste CSF from extraventricular drainage (EVD) from 29 children bearing different brain tumors and 17 controls needing EVD insertion for unrelated causes. 1598 and 1526 proteins were identified by liquid chromatography-coupled tandem mass spectrometry proteomics in CSF control and brain tumor patients, respectively, 263 and 191 proteins being exclusive of either condition. Bioinformatic analysis revealed promising protein biomarkers for the discrimination between control and tumor (TATA-binding protein-associated factor 15 and S100 protein B). Moreover, Thymosin beta-4 (TMSB4X) and CD109, and 14.3.3 and HSP90 alpha could discriminate among other brain tumors and low-grade gliomas plus glyoneuronal tumors/pilocytic astrocytoma, or embryonal tumors/medulloblastoma. Biomarkers were validated by ELISA assay. Our method was able to distinguish among brain tumor vs non-tumor/hemorrhagic conditions (controls) and to differentiate two large classes of brain tumors. Further prospective studies may assess whether the biomarkers proposed by our discovery approach can be identified in other bodily fluids, therefore less invasively, and are useful to guide therapy and predict recurrences.

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Profile of Brain Tumor Patients in 10 Hospitals in North Sumatera

Sumatera Medical Journal ◽

10.32734/sumej.v1i1.443 ◽

2018 ◽

Vol 1 (1) ◽

pp. 27-32

Author(s):

Aldy S. Rambe ◽

Aida Fitri ◽

Tonam Tonam

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Ct Scan ◽

Clinical Manifestations ◽

Motor Dysfunction ◽

Primary Data ◽

Tumor Patients ◽

Primary Tumors ◽

Common Cause ◽

Head Ct

Although brain tumors only 1.4% of all tumors, high fatality rate made these tumors need special attention. In North Sumatera, there is no data on brain tumors patients profile. Objective: To determine brain tumor patients’ profile in North Sumatera, Indonesia. Method: A descriptive hospital-based study with primary data which taken from September–December 2012. Result: Of 75 brain tumors patients surveyed in 10 hospitals in North Sumatera 38 (50.7%) patients were male and 37 (49.3%) patients were female. Mean of age was 51.45 (11–87) years old. Most of the subjects were housewifes, 26 (34.7%) patients. The most common cause that brought these patients to see doctors was headache 32 (42.7%), followed by decreased level of consciousness 17 (22.7%). Clinical manifestations found in these patients were headache 67 (89.3%), dizziness/vertigo 41 (54.7%), convulsion 22 (29.3%), vomitting 32 (42.7%), motor dysfunction 46 (61.3%), sensory dysfunction 21 (28%), and cognitive decline 21 (28%). Only 7 patients (9.3%) had history of tumor in his/her relatives. Eighteen patients (24%) were treated surgically and 8 (10.7%) were given radiotherapy. 71 patients were alive (94.7%) when discharged from the hospitals due to various reasons. Head CT Scan/MRI showed primary tumors in 56 (74.7%) patients. Of these primary tumors 25 (44.6%) patients were meningioma and 19 (33.9%) were astrocytoma. Of 19 (25.3%) patients with secondary tumor, most common primary tumor where found in the lung 11 (57.9%). Conclusion: Sex the patients were equally distributed with mean of age was 51.45 (11–87) years old. The most common cause that brought these patients to seek for treatment were headache. Most of these patients were treated conservatively. The most common head CT Scan/MRI findings showed primary tumors.

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Genetic variants and cognitive functions in patients with brain tumors

Neuro-Oncology ◽

10.1093/neuonc/noz094 ◽

2019 ◽

Vol 21 (10) ◽

pp. 1297-1309 ◽

Cited By ~ 5

Author(s):

Denise D Correa ◽

Jaya Satagopan ◽

Axel Martin ◽

Erica Braun ◽

Maria Kryza-Lacombe ◽

...

Keyword(s):

Oxidative Stress ◽

Cell Cycle ◽

Dna Repair ◽

Brain Tumor ◽

Brain Tumors ◽

Cell Cycle Regulation ◽

Cognitive Outcome ◽

Cholesterol Transport ◽

Tumor Patients ◽

Cycle Regulation

AbstractBackgroundPatients with brain tumors treated with radiotherapy (RT) and chemotherapy (CT) often experience cognitive dysfunction. We reported that single nucleotide polymorphisms (SNPs) in the APOE, COMT, and BDNF genes may influence cognition in brain tumor patients. In this study, we assessed whether genes associated with late-onset Alzheimer’s disease (LOAD), inflammation, cholesterol transport, dopamine and myelin regulation, and DNA repair may influence cognitive outcome in this population.MethodsOne hundred and fifty brain tumor patients treated with RT ± CT or CT alone completed a neurocognitive assessment and provided a blood sample for genotyping. We genotyped genes/SNPs in these pathways: (i) LOAD risk/inflammation/cholesterol transport, (ii) dopamine regulation, (iii) myelin regulation, (iv) DNA repair, (v) blood–brain barrier disruption, (vi) cell cycle regulation, and (vii) response to oxidative stress. White matter (WM) abnormalities were rated on brain MRIs.ResultsMultivariable linear regression analysis with Bayesian shrinkage estimation of SNP effects, adjusting for relevant demographic, disease, and treatment variables, indicated strong associations (posterior association summary [PAS] ≥ 0.95) among tests of attention, executive functions, and memory and 33 SNPs in genes involved in: LOAD/inflammation/cholesterol transport (eg, PDE7A, IL-6), dopamine regulation (eg, DRD1, COMT), myelin repair (eg, TCF4), DNA repair (eg, RAD51), cell cycle regulation (eg, SESN1), and response to oxidative stress (eg, GSTP1). The SNPs were not significantly associated with WM abnormalities.ConclusionThis novel study suggests that polymorphisms in genes involved in aging and inflammation, dopamine, myelin and cell cycle regulation, and DNA repair and response to oxidative stress may be associated with cognitive outcome in patients with brain tumors.

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Prognostic histopathologic features of canine glial tumors

Veterinary Pathology ◽

10.1177/03009858211025795 ◽

2021 ◽

pp. 030098582110257

Author(s):

Joshua L. Merickel ◽

G. Elizabeth Pluhar ◽

Aaron Rendahl ◽

M. Gerard O’Sullivan

Keyword(s):

Brain Tumor ◽

Median Survival ◽

Low Grade ◽

Astrocytic Tumors ◽

Translational Model ◽

Poor Survival ◽

Whole Brain ◽

Tumor Types ◽

Tumor Biopsies ◽

Prognostic Data

Gliomas are relatively common tumors in aged dogs (especially brachycephalic breeds), and the dog is proving to be useful as a translational model for humans with brain tumors. Hitherto, there is relatively little prognostic data for canine gliomas and none on outcome related to specific histological features. Histologic sections of tumor biopsies from 33 dogs with glioma treated with surgical resection and immunotherapy and 21 whole brains obtained postmortem were reviewed. Tumors were diagnosed as astrocytic, oligodendroglial, or undefined glioma using Comparative Brain Tumor Consortium criteria. Putative features of malignancy were evaluated, namely, mitotic counts, glomeruloid vascularization, and necrosis. For biopsies, dogs with astrocytic tumors lived longer than those with oligodendroglial or undefined tumor types (median survival 743, 205, and 144 days, respectively). Dogs with low-grade gliomas lived longer than those with high-grade gliomas (median survival 734 and 194 days, respectively). Based on analysis of tumor biopsies, low mitotic counts, absence of glomeruloid vascularization, and absence of necrosis correlated with increased survival (median 293, 223, and 220 days, respectively), whereas high mitotic counts, glomeruloid vascularization, and necrosis correlated with poor survival (median 190, 170, and 154 days, respectively). Mitotic count was the only histological feature in biopsy samples that significantly correlated with survival ( P < .05). Whole-brain analyses for those same histologic features had similar and more robust correlations, and were statistically significant for all features ( P < .05). The small size of biopsy samples may explain differences between biopsy and whole-brain tumor data. These findings will allow more accurate prognosis for gliomas.

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IBRDM: An Intelligent Framework for Brain Tumor Classification Using Radiomics- and DWT-based Fusion of MRI Sequences

ACM Transactions on Internet Technology ◽

10.1145/3434775 ◽

2022 ◽

Vol 22 (1) ◽

pp. 1-30

Author(s):

Rahul Kumar ◽

Ankur Gupta ◽

Harkirat Singh Arora ◽

Balasubramanian Raman

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Performance Metrics ◽

Tumor Classification ◽

Training Dataset ◽

Tumor Segmentation ◽

Discrete Wavelet ◽

Low Grade ◽

Brain Tumor Segmentation ◽

Mri Sequences

Brain tumors are one of the critical malignant neurological cancers with the highest number of deaths and injuries worldwide. They are categorized into two major classes, high-grade glioma (HGG) and low-grade glioma (LGG), with HGG being more aggressive and malignant, whereas LGG tumors are less aggressive, but if left untreated, they get converted to HGG. Thus, the classification of brain tumors into the corresponding grade is a crucial task, especially for making decisions related to treatment. Motivated by the importance of such critical threats to humans, we propose a novel framework for brain tumor classification using discrete wavelet transform-based fusion of MRI sequences and Radiomics feature extraction. We utilized the Brain Tumor Segmentation 2018 challenge training dataset for the performance evaluation of our approach, and we extract features from three regions of interest derived using a combination of several tumor regions. We used wrapper method-based feature selection techniques for selecting a significant set of features and utilize various machine learning classifiers, Random Forest, Decision Tree, and Extra Randomized Tree for training the model. For proper validation of our approach, we adopt the five-fold cross-validation technique. We achieved state-of-the-art performance considering several performance metrics, 〈 Acc , Sens , Spec , F1-score , MCC , AUC 〉 ≡ 〈 98.60%, 99.05%, 97.33%, 99.05%, 96.42%, 98.19% 〉, where Acc , Sens , Spec , F1-score , MCC , and AUC represents the accuracy, sensitivity, specificity, F1-score, Matthews correlation coefficient, and area-under-the-curve, respectively. We believe our proposed approach will play a crucial role in the planning of clinical treatment and guidelines before surgery.

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EPID-17. COMPARATIVE EPIDEMIOLOGY OF PRIMARY BRAIN TUMORS AMONG ADOLESCENTS AND YOUNG ADULTS (AYA)

Neuro-Oncology ◽

10.1093/neuonc/noab196.350 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi89-vi89

Author(s):

Nayan Lamba ◽

Bryan Iorgulescu

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Cox Regression ◽

Adolescent And Young Adult ◽

Lower Grade ◽

Diffuse Glioma ◽

Tumor Type ◽

Primary Brain Tumors ◽

Diffuse Gliomas ◽

Hiv Aids

Abstract INTRODUCTION We utilized national registry data to evaluate the unique epidemiology of primary adolescent and young adult (AYA) brain tumors according to the WHO2016 classification. METHODS AYA patients (15≤age≤39) presenting between 2004-2017 with a brain tumor were identified by ICD-O-3 coding from the National Cancer Database (comprising >70% of newly-diagnosed cancers in the U.S.), and compared to pediatric and adult populations. Epidemiology and overall survival (estimated by Kaplan-Meier techniques and multivariable Cox regression) were assessed by WHO2016 tumor type. RESULTS 108,705 AYA brain tumor patients were identified (56.9% female), compared to 23,928 pediatric (46.8% female) and 748,272 adult (55.6% female) patients. Among the 69.4% of AYA brain tumors with pathological diagnosis, diffuse gliomas (31.4%), sellar tumors (19.2%), and meningiomas (15.3%) predominated in both sexes. Diffuse glioma (31.4%), sellar (19.2%), cranial nerve (7.3%), and mesenchymal non-meningothelial (4.1%) tumors represented a greater proportion of AYA brain tumors than in either pediatric or adult populations. A majority of all intracranial GCTs (59.2%) and neuronal & mixed neuronal-glial tumors (51.6%) presented during AYA. Although the prevalence of diffuse gliomas was similar between AYAs and adults, AYA gliomas were more likely to be grade 2-3 astrocytomas (38.9% vs 14.3%) and oligodendrogliomas (19.3% vs 4.3%) than in adults. GBMs represented 76.0% of adult diffuse gliomas vs. only 25.7% of AYA diffuse gliomas, but with a similar prevalence of MGMT promoter methylation (40.8% vs 38.4%). Notably, 50.7% of AYA PCNSLs were associated with HIV/AIDS, vs only 7.1% in adults (p< 0.001). CONCLUSIONS The distribution, epidemiology, and survival outcomes of primary brain tumors in the AYA population are distinct from their pediatric and adult counterparts. Notably, AYA infiltrative gliomas were more often of lower grade than adults and AYA PCNSL were far more likely to be associated with HIV/AIDS. Primary brain tumors in AYA patients require specialized management.

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IMMU-14. REVEALING THE MANY MYELOID STATES IN HUMAN BRAIN TUMORS AND WAYS TO PERTURB THEM

Neuro-Oncology ◽

10.1093/neuonc/noab196.373 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi94-vi95

Author(s):

Tyler Miller ◽

Chadi El Farran ◽

Julia Verga ◽

Charles Couturier ◽

Zeyu Chen ◽

...

Keyword(s):

Brain Tumor ◽

Tumor Microenvironment ◽

Immune Cells ◽

Ex Vivo ◽

Myeloid Cells ◽

Human Tumor ◽

Myeloid Cell ◽

Low Grade ◽

Tumor Patients ◽

The Many

Abstract Recent breakthroughs in immunotherapy have revolutionized treatment for many types of cancer, but unfortunately trials of these therapies have failed to provide meaningful life-prolonging benefit for brain tumor patients, potentially due to abundant immunosuppressive myeloid cells in the tumor. Our ultimate goal is to reprogram immunosuppressive tumor associated myeloid cells to an antitumor state to enable effective immunotherapy. Towards this goal, we have deeply characterized the immune microenvironment of more than 50 primary high and low grade gliomas using high-throughput single-cell RNA-sequencing to reveal recurrent myeloid cell states and immunosuppressive programs across IDH1 wild-type and mutant tumors. We have also established a brain tumor organoid model from primary patient tissue that maintains all of the tumor microenvironment, including myeloid and other immune cells. We utilize the this model to functionally test data-driven reprogramming strategies and understand how they impact the states of tumor and immune cells in the ex vivo human tumor microenvironment.

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PS1 - 176 Where Have All the Fat Cells Gone? A Comparative Analysis of Adiposity Patterns in Childhood Brain Tumor Survivors and Non-Cancer Controls

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/cjn.2016.359 ◽

2016 ◽

Vol 43 (S4) ◽

pp. S11-S11 ◽

Cited By ~ 1

Author(s):

K.W. Wang ◽

E. Kearsley ◽

N. Falzone ◽

A. Fleming ◽

S. Burrow ◽

...

Keyword(s):

Physical Activity ◽

Brain Tumor ◽

Brain Tumors ◽

Survival Rates ◽

Visceral Adiposity ◽

Activity Levels ◽

Tumor Type ◽

Technological Advances ◽

Cardiometabolic Disorders ◽

Fried Foods

Brain tumors are the most common solid tumors in children in Canada. While technological advances have increased their survival rates, survivors of childhood brain tumors (SCBT) often develop obesity, which can reduce lifespan and quality of life. While adiposity is a known factor for cardiometabolic disorders in the general population, adiposity patterns in SCBT have not been determined. This study aims to investigate how adiposity patterns differ between SCBT and non-cancer controls, and how lifestyle and treatment factors may contribute to these patterns. Methods: Fifty-nine SCBT and 108 non-cancer controls were recruited from the clinics at McMaster Children’s Hospital. Sociodemographic and lifestyle details were collected using standardized tools to assess diet, physical activity, and sleep. Brain tumor type, location and treatment details were obtained from medical records. Total and visceral adiposity were determined by total fat mass (FM) as well as waist-to-hip (WHR) and waist-to-height ratio (WHTR). Results: SCBT have higher total and visceral adiposity, while BMI is similar to controls. Female SCBT who received radiotherapy and/or chemotherapy have higher adiposity. A dietary pattern of white bread and fried foods with low dark bread was positively associated with adiposity. Lower physical activity levels, but not sleep durations, were associated with higher adiposity. Conclusion: SCBT have higher visceral and total adiposity than non-cancer controls. Sex, chemoradiotherapy, high fat diet, and physical inactivity, can contribute to these adiposity patterns. These results provide multiple points of entry to design interventions that reduce adiposity, and may improve long-term outcomes in SCBT.

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