Prognostic Value of YKL-40 in Patients with Glioblastoma: a Systematic Review and Meta-analysis

Prognostic and predictive role of YKL-40 in anal squamous cell carcinoma: a serological and tissue-based analysis in a multicentric cohort

Introduction

Anal squamous cell carcinoma (ASC) is a rare gastrointestinal malignancy showing an increased incidence over the past decades. YKL-40 is an immune modulator and pro-angiogenetic factor that showed a promising prognostic and predictive potential in several malignancies, but limited data are available for ASC. This study aims to provide an extensive evaluation of the prognostic and predictive role of YKL-40 in a multicenter cohort of ASC patients.

Methods

We retrospectively retrieved 72 consecutive cases of ASC diagnosed between February 2011 and March 2021. Both serum and tissue protein expression of YKL-40 were assessed, the latter in ASC tumor cells and peritumor immune cells.

Results

Increased YKL-40 serum levels at the time of diagnosis were associated with older age (p = 0.035), presence of cardiovascular/metabolic comorbidities (p = 0.007), and death for any cause (p = 0.011). In addition, high serum levels of YKL-40 were associated with a poor prognosis (HR: 2.82, 95% CI: 1.01-7.84; p = 0.047). Protein expression of YKL-40 in ASC tumor cells was significantly associated with low tumor grade (p = 0.031), while the increased expression in peritumor immune cells was associated with a worse response of patients to chemoradiotherapy (p = 0.007). However, YKL-40 protein expression in ASC tumor cells or peritumor immune cells did not significantly impact patient overall survival.

Discussion

In conclusion, YKL-40 resulted a relevant prognostic (serum level) and predictive (tissue protein expression in peritumor immune cells) biomarker and can considerably improve ASC patient clinical management.

A Synopsis of Biomarkers in Glioblastoma: Past and Present

Accounting for 48% of malignant brain tumors in adults, glioblastoma has been of great interest in the last decades, especially in the biomolecular and neurosurgical fields, due to its incurable nature and notable neurological morbidity. The major advancements in neurosurgical technologies have positively influenced the extent of safe tumoral resection, while the latest progress in the biomolecular field of GBM has uncovered new potential therapeutical targets. Although GBM currently has no curative therapy, recent progress has been made in the management of this disease, both from surgical and molecular perspectives. The main current therapeutic approach is multimodal and consists of neurosurgical intervention, radiotherapy, and chemotherapy, mostly with temozolomide. Although most patients will develop treatment resistance and tumor recurrence after surgical removal, biomolecular advancements regarding GBM have contributed to a better understanding of this pathology and its therapeutic management. Over the past few decades, specific biomarkers have been discovered that have helped predict prognosis and treatment responses and contributed to improvements in survival rates.

Phase 1 dose expansion and biomarker study assessing first-in-class tumor microenvironment modulator VT1021 in patients with advanced solid tumors

BACKGROUND

Preclinical studies have demonstrated that VT1021, a first-in-class therapeutic agent, inhibits tumor growth via stimulation of thrombospondin-1 (TSP-1) and reprograms the tumor microenvironment. We recently reported data from the dose escalation part of a phase I study of VT1021 in solid tumors. Here, we report findings from the dose expansion phase of the same study.

METHODS

We analyzed the safety and tolerability, clinical response, and biomarker profile of VT1021 in the expansion portion of the phase I study (NCT03364400). Safety/tolerability is determined by adverse events related to the treatment. Clinical response is determined by RECIST v1.1 and iRECIST. Biomarkers are measured by multiplexed ion beam imaging and enzyme-linked immunoassay (ELISA).

RESULTS

First, we report the safety and tolerability data as the primary outcome of this study. Adverse events (AE) suspected to be related to the study treatment (RTEAEs) are mostly grade 1-2. There are no grade 4 or 5 adverse events. VT1021 is safe and well tolerated in patients with solid tumors in this study. We report clinical responses as a secondary efficacy outcome. VT1021 demonstrates promising single-agent clinical activity in recurrent GBM (rGBM) in this study. Among 22 patients with rGBM, the overall disease control rate (DCR) is 45% (95% confidence interval, 0.24-0.67). Finally, we report the exploratory outcomes of this study. We show the clinical confirmation of TSP-1 induction and TME remodeling by VT1021. Our biomarker analysis identifies several plasmatic cytokines as potential biomarkers for future clinical studies.

CONCLUSIONS

VT1021 is safe and well-tolerated in patients with solid tumors in a phase I expansion study. VT1021 has advanced to a phase II/III clinical study in glioblastoma (NCT03970447).

Epithelial Membrane Protein-3 and Chitinase-3-like Protein-1 as New Prognostic Predictors of Glioma, a Two-Gene Study

BACKGROUND

Glioblastoma multiforme is the most common primary intracranial tumor, with a high degree of malignancy, poor therapeutic effect, and poor prognosis. According to previous studies, CHI3L1 and EMP3 are two independent tumor predictors that are of great significance for the prognostic prediction of other tumors, and their expression levels may be related to the prognosis of glioma patients.

METHODS

using Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), the Chinese Glioma Genome Atlas (CGGA), cBioPortal, LinkedOmics, and other databases, 693 glioma patients were screened to analyze the relationship between EMP3 and CHI3L1 expression and prognosis in glioma patients.

RESULTS

low-grade glioma patients with a low expression of EMP3/CHI3L1 had a better prognosis, and the combination of EMP3/CHI3L1 is a new predictor for glioma patients.

CONCLUSION

We used the TCGA and CGGA databases to analyze the effect of EMP3 and CHI3L1 expression on the prognosis of glioma patients and their correlation with gene expression using bioinformation analysis. The results showed that low-grade glioma patients with a low expression of EMP3 and CHI3L1 had a better prognosis, and EMP3 and CHI3L1 co-expression genes were correlated. The combination of these two factors could be a new prognostic index for glioma patients.

Advances on Liquid Biopsy Analysis for Glioma Diagnosis

Gliomas comprise the most frequent primary central nervous system (CNS) tumors, characterized by remarkable genetic and epigenetic heterogeneity, difficulty in monitoring, and increased relapse and mortality rates. Tissue biopsy is an established method of tumor cell collection and analysis that enables diagnosis, classification of different tumor types, and prediction of prognosis upon confirmation of tumor's location for surgical removal. However, it is an invasive and often challenging procedure that cannot be used for frequent patient screening, detection of mutations, disease monitoring, or resistance to therapy. To this end, the minimally invasive procedure of liquid biopsy has emerged, allowing effortless tumor sampling and enabling continuous monitoring. It is considered a novel preferable way to obtain faster data on potential tumor risk, personalized diagnosis, prognosis, and recurrence evaluation. The purpose of this review is to describe the advances on liquid biopsy for glioma diagnosis and management, indicating several biomarkers that can be utilized to analyze tumor characteristics, such as cell-free DNA (cfDNA), cell-free RNA (cfRNA), circulating proteins, circulating tumor cells (CTCs), and exosomes. It further addresses the benefit of combining liquid biopsy with radiogenomics to facilitate early and accurate diagnoses, enable precise prognostic assessments, and facilitate real-time disease monitoring, aiming towards more optimal treatment decisions.

Recent advances in label-free optical, electrochemical, and electronic biosensors for glioma biomarkers

Gliomas are the most commonly occurring primary brain tumor with poor prognosis and high mortality rate. Currently, the diagnostic and monitoring options for glioma mainly revolve around imaging techniques, which often provide limited information and require supervisory expertise. Liquid biopsy is a great alternative or complementary monitoring protocol that can be implemented along with other standard diagnosis protocols. However, standard detection schemes for sampling and monitoring biomarkers in different biological fluids lack the necessary sensitivity and ability for real-time analysis. Lately, biosensor-based diagnostic and monitoring technology has attracted significant attention due to several advantageous features, including high sensitivity and specificity, high-throughput analysis, minimally invasive, and multiplexing ability. In this review article, we have focused our attention on glioma and presented a literature survey summarizing the diagnostic, prognostic, and predictive biomarkers associated with glioma. Further, we discussed different biosensory approaches reported to date for the detection of specific glioma biomarkers. Current biosensors demonstrate high sensitivity and specificity, which can be used for point-of-care devices or liquid biopsies. However, for real clinical applications, these biosensors lack high-throughput and multiplexed analysis, which can be achieved via integration with microfluidic systems. We shared our perspective on the current state-of-the-art different biosensor-based diagnostic and monitoring technologies reported and the future research scopes. To the best of our knowledge, this is the first review focusing on biosensors for glioma detection, and it is anticipated that the review will offer a new pathway for the development of such biosensors and related diagnostic platforms.

Functional analysis of the short splicing variant encoded by CHI3L1/YKL-40 in glioblastoma

The glycoprotein YKL-40 has been well studied as a serum biomarker of prognosis and disease status in glioblastoma. YKL-40 is a chitinase-like protein with defective chitinase activity that plays an important role in promoting cell proliferation, migration, and metastasis in glioblastoma multiforme (GBM). The short variant (SV) of YKL-40, generated by an alternative splicing event that splices out exon 8, was reported in the early developing human musculoskeletal system, although its role in GBM is still unknown. Our results showed that individual glioblastoma cell lines displayed increased expression of the short variant of YKL-40 after low serum treatment. In addition, unlike the full-length (FL) version, which was localized to all cell compartments, the short isoform could not be secreted and was localized only to the cytoplasm. Functionally, FL YKL-40 promoted cell proliferation and migration, whereas SV YKL-40 suppressed them. Transcriptome analysis revealed that these opposing roles of the two isoforms may be modulated by differentially regulating several oncogenic-related pathways, including p53, the G2/M checkpoint, and MYC-related signaling. This study may provide new ideas for the development of targeted anti-YKL-40 therapy in GBM treatment.

Chitinase 3-Like 2

OBJECTIVES

We aimed to evaluate the expression pattern of chitinase 3-like 2 (CHI3L2) in the tumor core and peritumoral brain zone (PBZ) of newly diagnosed glioblastoma (GBM) in recurrent tumors and its association with patient prognosis.

METHODS

The study was conducted on three sample sets derived from different patient cohorts. Messenger RNA (mRNA) expression of CHI3L2 in the tumor core and PBZ (n = 34) compared with control (n = 20) tissues was studied by quantitative polymerase chain reaction in sample set 1. Sample set 2 included 19 paired, primary-recurrent GBM tissues. Sample set 3 comprised 82 GBM tissues of patients with treatment and follow-up information. Immunohistochemistry (IHC) was performed on all three sample sets.

RESULTS

mRNA expression of CHI3L2 was significantly higher in the tumor core and PBZ compared with control (P < .0001). By IHC, CHI3L2 showed strong cytoplasmic staining in tumor cells. Recurrent tumors had a higher expression of CHI3L2 compared with primary tumors (P = .007). Survival analysis showed CHI3L2 expression was associated with shorter overall survival (P = .034) and progression-free survival (P = .010), which was in line with The Cancer Genome Atlas cohort (P = .043).

CONCLUSIONS

High expression of CHI3L2 in the tumor core and PBZ, as well as its association with tumor recurrence and poor patient prognosis, suggests it might be contributing to tumor spread and recurrence.

Molecular and Circulating Biomarkers in Patients with Glioblastoma

Glioblastoma is the most aggressive malignant tumor of the central nervous system with a low survival rate. The difficulty of obtaining this tumor material represents a major limitation, making the real-time monitoring of tumor progression difficult, especially in the events of recurrence or resistance to treatment. The identification of characteristic biomarkers is indispensable for an accurate diagnosis, the rigorous follow-up of patients, and the development of new personalized treatments. Liquid biopsy, as a minimally invasive procedure, holds promise in this regard. The purpose of this paper is to summarize the current literature regarding the identification of molecular and circulating glioblastoma biomarkers and the importance of their integration as a valuable tool to improve patient care.

Neurodegeneration and Glial Activation Related CSF Biomarker as the Diagnosis of Alzheimer's Disease: A Systematic Review and an Updated Meta-analysis

OBJECTIVE

Recently, neuron specific enolase (NSE), Visinin-like protein-1 (VLP-1), neurogranin (Ng), and YKL-40 have been identified as candidates for neuronal degeneration and glial activation biomarkers. Therefore, we perform a comprehensive meta-analysis to assess the diagnostic value of CSF NSE, VLP-1, Ng and YKL-40 in Alzheimer's disease (AD).

METHODS

We searched Pubmed, MEDLINE, EMBASE databases for research about the levels of CSF NSE, VLP-1, Ng and YKL-40 in AD patients compared with controls or other dementia diseases until Dec 2020.

RESULTS

The present meta-analysis contained a total of 51 studies comprising 6248 patients with dementia disorders and 3861 controls. Among them, there were 3262 patients with AD, 2456 patients with mild cognitive impairment (MCI), 173 patients with vascular dementia (VaD), 221 patients with frontotemporal dementia (FTD), and 136 with Lewy bodies dementia (DLB). Our study demonstrated that CSF NSE, VLP-1, Ng and YKL-40 levels were increased in AD as compared to healthy controls. We also observed that the CSF NSE level was higher in AD than VaD, suggesting CSF NSE might act as a key role in distinguishing between AD and VaD. Interestingly, there was a higher VLP-1 expression in AD, and a lower expression in DLB patients. Moreover, we found the CSF Ng level was increased in AD than MCI, implying CSF Ng might be a biomarker for identifying the progression of AD. Additionally, a significantly higher CSF YKL-40 level was detected not only in AD, but also in FTD, DLB, VaD, signifying YKL-40 was not sensitive in the diagnosis of AD.

CONCLUSION

Our study confirmed that CSF levels of NSE, VLP-1, and Ng could be valuable biomarkers for identifying patients who are more susceptible to AD and distinguishing AD from other neurodegenerative dementia disorders.

Ensemble based machine learning approach for prediction of glioma and multi-grade classification

Glioma is the most pernicious cancer of the nervous system, with histological grade influencing the survival of patients. Despite many studies on the multimodal treatment approach, survival time remains brief. In this study, a novel two-stage ensemble of an ensemble-type machine learning-based predictive framework for glioma detection and its histograde classification is proposed. In the proposed framework, five characteristics belonging to 135 subjects were considered: human telomerase reverse transcriptase (hTERT), chitinase-like protein (YKL-40), interleukin 6 (IL-6), tissue inhibitor of metalloproteinase-1 (TIMP-1) and neutrophil/lymphocyte ratio (NLR). These characteristics were examined using distinctive ensemble-based machine learning classifiers and combination strategies to develop a computer-aided diagnostic system for the non-invasive prediction of glioma cases and their grade. In the first stage, the analysis was conducted to classify glioma cases and control subjects. Machine learning approaches were applied in the second stage to classify the recognised glioma cases into three grades, from grade II, which has a good prognosis, to grade IV, which is also known as glioblastoma. All experiments were evaluated with a five-fold cross-validation method, and the classification results were analysed using different statistical parameters. The proposed approach obtained a high value of accuracy and other statistical parameters compared with other state-of-the-art machine learning classifiers. Therefore, the proposed framework can be utilised for designing other intervention strategies for the prediction of glioma cases and their grades.

Promoting Prognostic Model Application: A Review Based on Gliomas

Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.

Promoting Prognostic Model Application: A Review Based on Gliomas

Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.

Identifying cellular signalling molecules in developmental disorders of the brain: Evidence from focal cortical dysplasia and tuberous sclerosis

AIMS

We understand little of the pathogenesis of developmental cortical lesions, because we understand little of the diversity of the cell types that contribute to the diseases or how those cells interact. We tested the hypothesis that cellular diversity and cell-cell interactions play an important role in these disorders by investigating the signalling molecules in the commonest cortical malformations that lead to childhood epilepsy, focal cortical dysplasia (FCD) and tuberous sclerosis (TS).

METHODS

Transcriptional profiling clustered cases into molecularly distinct groups. Using gene expression data, we identified the secretory signalling molecules in FCD/TS and characterised the cell types expressing these molecules. We developed a functional model using organotypic cultures.

RESULTS

We identified 113 up-regulated secretory molecules in FCDIIB/TS. The top 12 differentially expressed genes (DEGs) were validated by immunohistochemistry. This highlighted two molecules, Chitinase 3-like protein 1 (CHI3L1) and C-C motif chemokine ligand 2 (CCL2) (MCP1) that were expressed in a unique population of small cells in close proximity to balloon cells (BC). We then characterised these cells and developed a functional model in organotypic slice cultures. We found that the number of CHI3L1 and CCL2 expressing cells decreased following inhibition of mTOR, the main aberrant signalling pathway in TS and FCD.

CONCLUSIONS

Our findings highlight previously uncharacterised small cell populations in FCD and TS which express specific signalling molecules. These findings indicate a new level of diversity and cellular interactions in cortical malformations and provide a generalisable approach to understanding cell-cell interactions and cellular heterogeneity in developmental neuropathology.

Perspective: targeting VEGF-A and YKL-40 in glioblastoma - matter matters

Glioblastomas (GBM) are heterogeneous highly vascular brain tumors exploiting the unique microenvironment in the brain to resist treatment and anti-tumor responses. Anti-angiogenic agents, immunotherapy, and targeted therapy have been studied extensively in GBM patients over a number of decades with minimal success. Despite maximal efforts, prognosis remains dismal with an overall survival of approximately 15 months.

Bevacizumab, a humanized anti-vascular endothelial growth factor (VEGF) antibody, underwent accelerated approval by the U.S. Food and Drug Administration in 2009 for the treatment of recurrent GBM based on promising preclinical and early clinical studies. Unfortunately, subsequent clinical trials did not find overall survival benefit. Pursuing pleiotropic targets and leaning toward multitarget strategies may be a key to more effective therapeutic intervention in GBM, but preclinical evaluation requires careful consideration of model choices. In this study, we discuss bevacizumab resistance, dual targeting of pro-angiogenic modulators VEGF and YKL-40 in the context of brain tumor microenvironment, and how model choice impacts study conclusions and its translational significance.

Potential biomarkers and challenges in glioma diagnosis, therapy and prognosis

Gliomas are the most common central nervous system malignancies and present with significant morbidity and mortality. Treatment modalities are currently limited to surgical resection, chemotherapy and radiotherapy. Increases in survival rate over the previous decades are negligible, further pinpointing an unmet clinical need in this field. There is a continual struggle with the development of effective glioma diagnostics and therapeutics, largely due to a multitude of factors, including the presence of the blood–brain barrier and significant intertumoural and intratumoural heterogeneity. Importantly, there is a lack of reliable biomarkers for glioma, particularly in aiding tumour subtyping and measuring response to therapy. There is a need for biomarkers that would both overcome the complexity of the disease and allow for a minimally invasive means of detection and analysis. This is a comprehensive review evaluating the potential of current cellular, proteomic and molecular biomarker candidates for glioma. Significant hurdles faced in glioma diagnostics and therapy are also discussed here.

Prognostic value of YKL-40 in solid tumors: a meta-analysis of 41 cohort studies

Background

Serum/plasma YKL-40 can be a useful index that is associated with tumor development. However, the prognostic value of serum/plasma YKL-40 in patients with solid tumors is still unclear. We aimed to utilize the existing literature to investigate the prognostic value of serum/plasma YKL-40 in solid tumors.

Methods

An extensive literature search for relevant studies was conducted with the Embase, Medline and Web of Science databases. The effect on survival was measured with the hazard ratio (HR). Then, pooled HRs and 95% confidence intervals (CIs) were calculated using the random and fixed-effects models according to the heterogeneity of the included studies.

Results

This meta-analysis was based on 41 publications and comprised a total of 7762 patients with solid tumors. The pooled HR showed that elevated serum/plasma YKL-40 was significantly associated with poor OS (HR, 1.44; 95% CI 1.33–1.56). We also found that elevated serum/plasma YKL-40 had significant prognostic effects on OS in various cancer subgroups such as gastrointestinal tumors (HR, 1.37; 95% CI 1.18–1.58), ovarian cancer (HR, 2.27; 95% CI 1.69–3.06), melanoma (HR, 1.77; 95% CI 1.18–2.67), lung cancer (HR, 1.73; 95% CI 1.35–2.23), urologic neoplasms (HR, 1.61; 95% CI 1.08–2.40) and glioblastoma (HR, 1.23; 95% CI 1.07–1.42); in contrast, the prognostic effect of serum/plasma YKL-40 was not statistically significant in breast cancer (HR, 1.07; 95% CI 0.98–1.17).

Conclusions

The available evidence supports the hypothesis that elevated serum/plasma YKL-40 is associated with poor survival in patients with solid tumors and that serum/plasma YKL-40 may serve as a novel prognostic biomarker.

Liquid Biopsy in Glioblastoma: Opportunities, Applications and Challenges

Liquid biopsy represents a minimally invasive procedure that can provide similar information from body fluids to what is usually obtained from a tissue biopsy sample. Its implementation in the clinical setting might significantly renew the field of medical oncology, facilitating the introduction of the concepts of precision medicine and patient-tailored therapies. These advances may be useful in the diagnosis of brain tumors that currently require surgery for tissue collection, or to perform genetic tumor profiling for disease classification and guidance of therapy. In this review, we will summarize the most recent advances and putative applications of liquid biopsy in glioblastoma, the most common and malignant adult brain tumor. Moreover, we will discuss the remaining challenges and hurdles in terms of technology and biology for its clinical application.

CHI3L1, NTRK2, 1p/19q and IDH Status Predicts Prognosis in Glioma

The aim of this study was to identify relevant biomarkers for the prognosis of glioma considering current molecular changes such as IDH mutation and 1p19q deletion. Gene expression profiling was performed using the TaqMan Low Density Array and hierarchical clustering using 96 selected genes in 64 patients with newly diagnosed glioma. The expression dataset was validated on a large independent cohort from The Cancer Genome Atlas (TCGA) database. A differential expression panel of 26 genes discriminated two prognostic groups regardless of grade and molecular groups of tumors: Patients having a poor prognosis with a median overall survival (OS) of 23.0 ± 9.6 months (group A) and patients having a good prognosis with a median OS of 115.0 ± 6.6 months (group B) (p = 0.007). Hierarchical clustering of the glioma TCGA cohort supported the prognostic value of these 26 genes (p < 0.0001). Among these genes, CHI3L1 and NTRK2 were identified as factors that can be associated with IDH status and 1p/19q co-deletion to distinguish between prognostic groups of glioma from the TCGA cohort. Therefore, CHI3L1 associated with NTRK2 seemed to be able to provide new information on glioma prognosis.

Astrogliogenesis in human fetal brain: complex spatiotemporal immunoreactivity patterns of GFAP, S100, AQP4 and YKL-40

The astroglial lineage consists of heterogeneous cells instrumental for normal brain development, function and repair. Unfortunately, this heterogeneity complicates research in the field, which suffers from lack of truly specific and sensitive astroglial markers. Nevertheless, single astroglial markers are often used to describe astrocytes in different settings. We therefore investigated and compared spatiotemporal patterns of immunoreactivity in developing human brain from 12 to 21 weeks post conception and publicly available RNA expression data for four established and potential astroglial markers - GFAP, S100, AQP4 and YKL-40. In the hippocampal region, we also screened for C3, a complement component highly expressed in A1-reactive astrocytes. We found diverging partly overlapping patterns of the established astroglial markers GFAP, S100 and AQP4, confirming that none of these markers can fully describe and discriminate different developmental forms and subpopulations of astrocytes in human developing brain, although AQP4 seems to be the most sensitive and specific marker for the astroglial lineage at midgestation. AQP4 characterizes a brain-wide water transport system in cerebral cortex with regional differences in immunoreactivity at midgestation. AQP4 distinguishes a vast proportion of astrocytes and subpopulations of radial glial cells destined for the astroglial lineage, including astrocytes determined for the future glia limitans and apical truncated radial glial cells in ganglionic eminences, devoid of GFAP and S100. YKL-40 and C3d, previously found in reactive astrocytes, stain different subpopulations of astrocytes/astroglial progenitors in developing hippocampus at midgestation and may characterize specific subpopulations of 'developmental astrocytes'. Our results clearly reflect that lack of pan-astrocytic markers necessitates the consideration of time, region, context and aim when choosing appropriate astroglial markers.

Clinical utility of pleural fluid YKL-40 as a marker of malignant pleural effusion

Pleural effusion is a common presenting feature of malignancy. Malignant pleural effusion is primarily diagnosed by pleural fluid cytology, pleural biopsy, and tumor markers. The glycoprotein YKL-40 is a new tumor marker that has shown to have a good diagnostic accuracy to detect malignant pleural effusion. However, there are only a few studies that have evaluated pleural fluid YKL-40 for detecting malignant pleural effusions. Hence, we conducted this study to evaluate the utility of pleural fluid YKL-40 to detect malignant pleural effusion. This is a cross-sectional study conducted between February 2016 and December 2017 in a tertiary care referral hospital. One hundred and forty-seven consecutive patients with pleural effusion were included in the study. These patients were divided into 3 groups, viz malignant, tuberculous, and parapneumonic pleural effusion, based on clinical features, radiological examination, and pleural fluid analysis. Pleural fluid YKL-40 levels were measured using enzyme-linked immunosorbent assay. Out of the 147 consecutive patients included in the study, 47 patients (31.97%) had malignant pleural effusion, 51 patients (34.69%) had tuberculous pleural effusion, and 49 patients (33.33%) had parapneumonic pleural effusion. The median pleural fluid YKL-40 level was higher in malignant pleural effusion (114.80 ng/mL) compared to tuberculous (93.17 ng/mL) and parapneumonic pleural effusion (89.87 ng/mL; P < 0.05). A diagnostic cut-off for pleural fluid YKL-40 value of 99.76 ng/mL detected malignant pleural effusion with 83% sensitivity, 87% specificity, positive predictive value (PPV) of 75%, negative predictive value (NPV) of 91.58%, and diagnostic accuracy of 85.71%. The level of pleural fluid YKL-40 is significantly elevated in malignant pleural effusion. In lymphocytic pleural effusions presenting with low adenosine deaminase levels and high YKL-40 levels, a thorough diagnostic search for malignancy is warranted.

Elevated YKL-40 expression is associated with a poor prognosis in breast cancer patients

Numerous studies have investigated the prognostic role of YKL-40 in breast cancer, but yielded inconsistent results. To derive a more precise evaluation, relevant publications assessing the association between YKL-40 expression and clinical outcome of breast cancer patients were electronically searched and identified. A combined analysis of included studies was performed using fixed- or random-effect model to calculate the pooled hazard ratio (HR) or odds ratio(OR) and 95% confidence interval (95%CI) for the assessment of the association. Ten eligible studies involving 1250 patients were ultimately included in the meta-analysis. Overall, the pooled analysis showed that elevated YKL-40 expression was significantly associated with a poor overall survival(OS: HR=1.48, 95%CI= 1.11-1.97) and disease-free survival(DFS: HR=1.51, 95%CI= 1.10-2.07). The subgroup analysis by detection methods revealed an unfavorable OS in breast cancer patients with elevated YKL-40 expression evaluated by IHC(HR=1.39, 95%CI=1.12-1.71) but not by ELISA/RIA. Also, the stratification analysis by ethnicity showed a significant association between increased YKL-40 expression and shorter OS of breast cancer patients in western population(HR=1.51, 95%CI=1.03-2.21) as well as Asian population (HR=1.40, 95%CI= 1.05-1.86). Similarly, the subgroup analysis by detection methods revealed a significantly inferior DFS in breast cancer patients with increased YKL-40 expression disregarding the use of IHC(HR=2.02, 95%CI=1.47-2.79) or ELISA/RIA(HR=1.06, 95%CI= 1.02 -1.10). Additionally, increased YKL-40 expression was found to significantly correlate with larger tumor size (OR=2.38, 95%CI=1.41-4.05).The present meta-analysis indicate that elevated YKL-40 expression is associated with a poor prognosis in breast cancer patients. YKL-40 may serve as a promising predictive biomarker of prognosis of breast cancer.

YKL-40 in the brain and cerebrospinal fluid of neurodegenerative dementias

BACKGROUND

YKL-40 (also known as Chitinase 3-like 1) is a glycoprotein produced by inflammatory, cancer and stem cells. Its physiological role is not completely understood but YKL-40 is elevated in the brain and cerebrospinal fluid (CSF) in several neurological and neurodegenerative diseases associated with inflammatory processes. Yet the precise characterization of YKL-40 in dementia cases is missing.

METHODS

In the present study, we comparatively analysed YKL-40 levels in the brain and CSF samples from neurodegenerative dementias of different aetiologies characterized by the presence of cortical pathology and disease-specific neuroinflammatory signatures.

RESULTS

YKL-40 was normally expressed in fibrillar astrocytes in the white matter. Additionally YKL-40 was highly and widely expressed in reactive protoplasmic cortical and perivascular astrocytes, and fibrillar astrocytes in sporadic Creutzfeldt-Jakob disease (sCJD). Elevated YKL-40 levels were also detected in Alzheimer's disease (AD) but not in dementia with Lewy bodies (DLB). In AD, YKL-40-positive astrocytes were commonly found in clusters, often around β-amyloid plaques, and surrounding vessels with β-amyloid angiopathy; they were also distributed randomly in the cerebral cortex and white matter. YKL-40 overexpression appeared as a pre-clinical event as demonstrated in experimental models of prion diseases and AD pathology. CSF YKL-40 levels were measured in a cohort of 288 individuals, including neurological controls (NC) and patients diagnosed with different types of dementia. Compared to NC, increased YKL-40 levels were detected in sCJD (p < 0.001, AUC = 0.92) and AD (p < 0.001, AUC = 0.77) but not in vascular dementia (VaD) (p > 0.05, AUC = 0.71) or in DLB/Parkinson's disease dementia (PDD) (p > 0.05, AUC = 0.70). Further, two independent patient cohorts were used to validate the increased CSF YKL-40 levels in sCJD. Additionally, increased YKL-40 levels were found in genetic prion diseases associated with the PRNP-D178N (Fatal Familial Insomnia) and PRNP-E200K mutations.

CONCLUSIONS

Our results unequivocally demonstrate that in neurodegenerative dementias, YKL-40 is a disease-specific marker of neuroinflammation showing its highest levels in prion diseases. Therefore, YKL-40 quantification might have a potential for application in the evaluation of therapeutic intervention in dementias with a neuroinflammatory component.