Liquid biopsy for CNS lymphoma: CSF exosomes and CSF exosomal miR-15a, miR-21, miR-155, miR-210, and miR-19b are promising biomarkers for diagnosis.

BACKGROUND: Central nervous system lymphoma (CNSL) is a devastating disease with a poor prognosis. Early diagnosis, monitoring of the treatment response, and outcome prediction carry the utmost importance in the management of patients with CNSL. Surgical biopsy is the gold standard for tissue diagnosis, however, this procedure has potential complications. Therefore, there is a need for a method that provides information about diagnosis and patient monitoring to avoid surgical risks. The study aimed to investigate potential diagnostic biomarkers for patients with CNSL. METHODS AND RESULTS: Patients with secondary CNSL were included in this study. Serum and cerebrospinal fluid (CSF) samples were collected before treatment and after completion of the treatment. Cell-free DNA (cfDNA), exosomes, free and exosomal microRNA (miR)-15a, miR-21, miR-155, miR-210, and miR-19b in both serum and CSF were examined, and they were compared with the controls. Also, their levels before and after treatment were compared. Nine patients with the diagnosis of secondary CNSL were reviewed. cfDNA, miR-15a, and miR-155 in serum, and exosome in CSF were found to be significantly higher in CNSL patients compared to the controls. Exosomal miR-15a, miR-21, miR-155, miR-210, and miR-19b in CSF were found to be significantly higher in CNSL patients compared to controls, whereas their levels in serum were not significantly high. CONCLUSIONS: Our findings suggested that exosomes and exosomal miR-15a, miR-21, miR-155, miR-210 and miR-19b in CSF would be promising biomarkers for the diagnosis of patients with CNSL. Further studies are needed to confirm our findings.

Metabolomic profile of cerebrospinal fluid from patients with diffuse gliomas.

BACKGROUND: Diffuse gliomas are among the most common brain tumors in adults and are associated with a dismal prognosis, especially in patients with glioblastoma. To date, tumor tissue acquisition is mandatory for conclusive diagnosis and therapeutic decision-making. In this study, we aimed to identify possible diagnostic and prognostic biomarkers in cerebrospinal fluid (CSF) and blood. METHODS: During glioma surgery at our institution, CSF and blood samples were collected from patients. Subsequently, targeted metabolomics analysis was used to detect and quantify circulating metabolites. The metabolome profiles of glioma patients were compared with those of patients in a control group who had undergone neurosurgery for other entities, such as nonglial tumors or hydrocephalus, and were correlated with established glioma diagnostic molecular markers. RESULTS: In this study, a total of 30 glioma patients were included, along with a control group of 21 patients without glioma. Serum metabolomic analysis did not detect any significant differences between the groups, whereas CSF-metabolome analysis revealed increased levels of six metabolites in glioma patients. Among these, the most pronounced differences were found for the biogenic amine putrescine (p = 0.00005). p-Cresol sulfate was identified as a potential CSF marker for determining isocitrate dehydrogenase (IDH) status in glioma patients (p = 0.0037). CONCLUSION: CSF-metabolome profiling, unlike blood profiling, shows promise as a diagnostic tool for glioma patients with the potential to assign molecular subtypes. The next step will involve a larger multicenter study to validate these findings, with the ultimate objective of integrating CSF metabolomics analysis into clinical practice.

Real-world experience with circulating tumor DNA in cerebrospinal fluid from patients with central nervous system tumors.

The characterization of genetic alterations in tumor samples has become standard practice for many human cancers to achieve more precise disease classification and guide the selection of targeted therapies. Cerebrospinal fluid (CSF) can serve as a source of tumor DNA in patients with central nervous system (CNS) cancer. We performed comprehensive profiling of CSF circulating tumor DNA (ctDNA) in 711 patients using an FDA-authorized platform (MSK-IMPACT™) in a hospital laboratory. We identified genetic alterations in 489/922 (53.0%) CSF samples with clinically documented CNS tumors. None of 85 CSF samples from patients without CNS tumors had detectable ctDNA. The distribution of clinically actionable somatic alterations was consistent with tumor-type specific alterations across the AACR GENIE cohort. Repeated CSF ctDNA examinations from the same patients identified clonal evolution and emergence of resistance mechanisms. ctDNA detection was associated with shortened overall survival following CSF collection. Next-generation sequencing of CSF, collected through a minimally invasive lumbar puncture in a routine hospital setting, provides clinically actionable cancer genotype information in a large fraction of patients with CNS tumors.

The causal relationship between CSF metabolites and GBM: a two-sample mendelian randomization analysis.

BACKGROUND: Glioblastoma multiforme (GBM) is a highly aggressive primary malignant brain tumor characterized by rapid progression, poor prognosis, and high mortality rates. Understanding the relationship between cerebrospinal fluid (CSF) metabolites and GBM is crucial for identifying potential biomarkers and pathways involved in the pathogenesis of this devastating disease. METHODS: In this study, Mendelian randomization (MR) analysis was employed to investigate the causal relationship between 338 CSF metabolites and GBM. The data for metabolites were obtained from a genome-wide association study summary dataset based on 291 individuals, and the GBM data was derived from FinnGen included 91 cases and 174,006 controls of European descent. The Inverse Variance Weighted method was utilized to estimate the causal effects. Supplementary comprehensive assessments of causal effects between CSF metabolites and GBM were conducted using MR-Egger regression, Weighted Median, Simple Mode, and Weighted Mode methods. Additionally, tests for heterogeneity and pleiotropy were performed. RESULTS: Through MR analysis, a total of 12 identified metabolites and 2 with unknown chemical properties were found to have a causal relationship with GBM. 1-palmitoyl-2-stearoyl-gpc (16:0/18:0), 7-alpha-hydroxy-3-oxo-4-cholestenoate, Alpha-tocopherol, Behenoyl sphingomyelin (d18:1/22:0), Cysteinylglycine, Maleate, Uracil, Valine, X-12,101, X-12,104 and Butyrate (4:0) are associated with an increased risk of GBM. N1-methylinosine, Stachydrine and Succinylcarnitine (c4-dc) are associated with decreased GBM risk. CONCLUSION: In conclusion, this study sheds light on the intricate interplay between CSF metabolites and GBM, offering novel perspectives on disease mechanisms and potential treatment avenues. By elucidating the role of CSF metabolites in GBM pathogenesis, this research contributes to the advancement of diagnostic capabilities and targeted therapeutic interventions for this aggressive brain tumor. Further exploration of these findings may lead to improved management strategies and better outcomes for patients with GBM.

Proteomic profiling of cerebrospinal fluid reveals TKT as a potential biomarker for medulloblastoma.

Cerebrospinal fluid (CSF) plays an important role in brain tumors, including medulloblastoma (MBL). Recent advancements in mass spectrometry systems and 'Omics' data analysis methods enable unbiased, high proteome depth research. We conducted proteomic profiling of the total CSF in MBL patients with the purpose of finding a potential diagnostic biomarker for MBL. We quantified 1112 proteins per CSF sample. Feature selection identified four elevated soluble proteins (SPTBN1, HSP90AA1, TKT, and NME1-NME2) in MBL CSF. Validation with ELISA confirmed that TKT was significantly elevated in MBL. Additionally, TKT-positive extracellular vesicles were significantly enriched in MBL CSF and correlated with the burden of leptomeningeal seeding. Our results provide insights into the proteomics data of the total CSF of MBL patients. Furthermore, we identified the significance of TKT within the total CSF and its presence within circulating EVs in the CSF. We suggest that TKT may serve as a biomarker for MBL.

Monitoring pediatric CNS non-germinomatous germ cell tumors via cerebrospinal fluid circulating tumor DNA.

BACKGROUND: Accurate molecular and clinical stratification of patients with central nervous system (CNS) non-germinomatous germ cell tumors (NGGCTs) remains challenging, impeding the development of personalized therapeutic approaches. Herein, we investigated the translational significance of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) in pediatric NGGCTs to identify characteristic features of CNS NGGCTs and to identify a subset of patients for whom the presence of residual disease is a risk factor and an indicator of shorter progression-free survival (PFS) and overall survival (OS). METHODS: Medical records of patients with CNS NGGCTs between January 1, 2018 and December 31, 2022 were reviewed retrospectively. RESULTS: The cohort consisted of 11 male and six female patients. Tumor markers were elevated in four of the five people who underwent surgery. The remaining 12 patients were diagnosed with malignant NGGCTs according to elevated tumor markers. Among them, ctDNA before chemotherapy as well as ctDNA clearance were consistently associated with PFS and OS (p < .05). By setting a ctDNA positivity threshold of 6%, patients with high ctDNA (above the threshold) levels, which had limitation due to the selection based on optimal statistic from the survival analysis, had significantly inferior 5-year PFS and OS compared to those with low levels (below the threshold). ctDNA or ctDNA clearance combined with the presence of residual disease predicted significantly worse OS and PFS (p < .05). CONCLUSIONS: CSF ctDNA might allow the study of genomic evolution and the characterization of tumors in pediatric NGGCTs. CSF ctDNA analysis may facilitate the clinical management of pediatric NGGCT patients, and aid in designing personalized therapeutic strategies.

Targeted multiplex validation of CSF proteomic biomarkers: implications for differentiation of PCNSL from tumor-free controls and other brain tumors.

Introduction: Primary central nervous system lymphoma (PCNSL) is a rare type of non-Hodgkin's lymphoma that affects brain parenchyma, eyes, cerebrospinal fluid, and spinal cord. Diagnosing PCNSL can be challenging because imaging studies often show similar patterns as other brain tumors, and stereotactic brain lesion biopsy conformation is invasive and not always possible. This study aimed to validate a previous proteomic profiling (PMID: 32610669) of cerebrospinal fluid (CSF) and develop a CSF-based proteomic panel for accurate PCNSL diagnosis and differentiation. Methods: CSF samples were collected from patients of 30 PCNSL, 30 other brain tumors, and 31 tumor-free/benign controls. Liquid chromatography tandem-mass spectrometry targeted proteomics analysis was used to establish CSF-based proteomic panels. Results: Final proteomic panels were selected and optimized to diagnose PCNSL from tumor-free controls or other brain tumor lesions with an area under the curve (AUC) of 0.873 (95%CI: 0.723-0.948) and 0.937 (95%CI: 0.807- 0.985), respectively. Pathways analysis showed diagnosis panel features were significantly enriched in pathways related to extracellular matrices-receptor interaction, focal adhesion, and PI3K-Akt signaling, while prion disease, mineral absorption and HIF-1 signaling were significantly enriched with differentiation panel features. Discussion: This study suggests an accurate clinical test panel for PCNSL diagnosis and differentiation with CSF-based proteomic signatures, which may help overcome the challenges of current diagnostic methods and improve patient outcomes.

Establishing the utility of multi-platform liquid biopsy by integrating the CSF methylome and proteome in CNS tumours.

BACKGROUND: Liquid biopsy represents a major development in cancer research, with significant translational potential. Similarly, it is increasingly recognized that multi-omic molecular approaches are a powerful avenue through which to understand complex and heterogeneous disease biology. We hypothesize that merging these two promising frontiers of cancer research will improve the discriminatory capacity of current models and allow for improved clinical utility. METHODS: We have compiled a cohort of patients with glioblastoma, brain metastasis, and primary central nervous system lymphoma. Cell-free methylated DNA immunoprecipitation (cfMeDIP) and shotgun proteomic profiling was obtained from the cerebrospinal fluid (CSF) of each patient and used to build tumour-specific classifiers. RESULTS: We show that the DNA methylation and protein profiles of cerebrospinal fluid can be integrated to fully discriminate lymphoma from its diagnostic counterparts with perfect AUC of 1 (95% confidence interval 1-1) and 100% specificity, significantly outperforming single-platform classifiers. CONCLUSIONS: We present the most specific and accurate CNS lymphoma classifier to date and demonstrates the synergistic capability of multi-platform liquid biopsies. This has far-reaching translational utility for patients with newly diagnosed intra-axial brain tumours.

Biomarkers in Cerebrospinal Fluid for the Diagnosis and Monitoring of Gliomas.

Gliomas are the most common type of malignant brain tumor and are characterized by a plethora of heterogeneous molecular alterations. Current treatments require the emergence of reliable biomarkers that will aid personalized treatment decisions and increase life expectancy. Glioma tissues are not as easily accessible as other solid tumors; therefore, detecting prominent biomarkers in biological fluids is necessary. Cerebrospinal fluid (CSF) circulates adjacent to the cerebral parenchyma and holds promise for discovering useful prognostic, diagnostic, and predictive biomarkers. In this review, we summarize extensive research regarding the role of circulating DNA, tumor cells, proteins, microRNAs, metabolites, and extracellular vesicles as potential CSF biomarkers for glioma diagnosis, prognosis, and monitoring. Future studies should address discrepancies and issues of specificity regarding CSF biomarkers, as well as the validation of candidate biomarkers.

Primary diffuse large B-cell lymphoma of the central nervous system identified with CSF biomarkers.

BACKGROUND: Diagnosis of primary diffuse large B-cell lymphoma of the central nervous system (PCNSL) is challenging and often delayed. MRI imaging, CSF cytology and flow cytometry have a low sensitivity and even brain biopsies can be misleading. We report three cases of PCNSL with various clinical presentation and radiological findings where the diagnosis was suggested by novel CSF biomarkers and subsequently confirmed by brain biopsy or autopsy. CASE PRESENTATIONS: The first case is a 79-year-old man with severe neurocognitive dysfunction and static ataxia evolving over 5 months. Brain MRI revealed a nodular ventriculitis. An open brain biopsy was inconclusive. The second case is a 60-year-old woman with progressive sensory symptoms in all four limbs, evolving over 1 year. Brain and spinal MRI revealed asymmetric T2 hyperintensities of the corpus callosum, corona radiata and corticospinal tracts. The third case is a 72-year-old man recently diagnosed with primary vitreoretinal lymphoma of the right eye. A follow-up brain MRI performed 4 months after symptom onset revealed a T2 hyperintense fronto-sagittal lesion, with gadolinium uptake and perilesional edema. In all three cases, CSF flow cytometry and cytology were negative. Mutation analysis on the CSF (either by digital PCR or by next generation sequencing) identified the MYD88 L265P hotspot mutation in all three cases. A B-cell clonality study, performed in case 1 and 2, identified a monoclonal rearrangement of the immunoglobulin light chain lambda (IGL) and kappa (IGK) gene. CSF CXCL-13 and IL-10 levels were high in all three cases, and IL-10/IL-6 ratio was high in two. Diagnosis of PCNSL was later confirmed by autopsy in case 1, and by brain biopsy in case 2 and 3. CONCLUSIONS: Taken together, 5 CSF biomarkers (IL-10, IL-10/IL-6 ratio, CXCL13, MYD88 mutation and monoclonal IG gene rearrangements) were strongly indicative of a PCNSL. Using innovative CSF biomarkers can be sensitive and complementary to traditional CSF analysis and brain biopsy in the diagnosis of PCNSL, potentially allowing for earlier diagnosis and treatment.

Logistic regression modeling of cytokines for cerebrospinal fluid evaluation in primary central nervous system lymphoma.

BACKGROUND: The diagnostic utility of cerebrospinal fluid (CSF) cytology encounters impediments stemming from variability in cell collection techniques and pathologists' morphological acumen, resulting in wide-ranging CSF positivity rates for primary central nervous system lymphomas (PCNSL). Such disparity impacts patient evaluation, treatment stratagem, and prognostication. Thus, this study endeavors to explore liquid biomarkers complementary to CSF cytology or immunophenotype analysis in the diagnosis of CSF involvement. METHODS: 398 newly diagnosed PCNSL patients were categorized into CSF involvement and non-involvement groups based on CSF cytology and immunophenotype analysis. Binary logistic regression analysis was performed on 338 patients to investigate factors predicting CSF involvement and to develop a joint prediction model. An additional cohort of 60 PCNSL patients was recruited for model validation. Statistical analyses included the Mann-Whitney U test for comparing various CSF parameters between two groups. ROC curve analyses were performed for each biomarker to identify PCNSL CSF involvement. RESULTS: The cytokine IL-10 level in CSF has emerged as the most promising biomarker for CSF evaluation, boasting an ROC AUC of 0.922. C-TNFα and soluble C-IL2R demonstrate efficacy in quantifying tumor burden within the CSF. Logistic regression identified C-IL10lg (OR = 30.103, P < 0.001), C-TNC (OR = 1.126, P < 0.001), C-IL2Rlg (OR = 3.743, P = 0.029) as independent predictors for CSF involvement, contributing to a joint predictive model with an AUC of 0.935, sensitivity of 74.1 %, and specificity of 93.0 %. Validation of the model in an independent cohort confirmed its effectiveness, achieving an AUC of 0.9713. CONCLUSIONS: The identification of these feasible biomarkers and the development of an accurate prediction model may facilitate the precise evaluation of CSF status in PCNSL, offering significant advancements in patient management.

Diagnosis of pediatric central nervous system tumors using methylation profiling of cfDNA from cerebrospinal fluid.

Pediatric central nervous system tumors remain challenging to diagnose. Imaging approaches do not provide sufficient detail to discriminate between different tumor types, while the histopathological examination of tumor tissue shows high inter-observer variability. Recent studies have demonstrated the accurate classification of central nervous system tumors based on the DNA methylation profile of a tumor biopsy. However, a brain biopsy holds significant risk of bleeding and damaging the surrounding tissues. Liquid biopsy approaches analyzing circulating tumor DNA show high potential as an alternative and less invasive tool to study the DNA methylation pattern of tumors. Here, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the circulating cell-free DNA (cfDNA) in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected cerebrospinal fluid samples from 19 pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. Analyses on the cfDNA showed high variability of cfDNA quantities across patients ranging from levels below the limit of quantification to 40 ng cfDNA per milliliter of CSF. Classification based on methylation profiling of cfDNA from CSF was correct for 7 out of 20 samples in our cohort. Accurate results were mostly observed in samples of high quality, more specifically those with limited high molecular weight DNA contamination. Interestingly, we show that centrifugation of the CSF prior to processing increases the fraction of fragmented cfDNA to high molecular weight DNA. In addition, classification was mostly correct for samples with high tumoral cfDNA fraction as estimated by computational deconvolution (> 40%). In summary, analysis of cfDNA in the CSF shows potential as a tool for diagnosing pediatric nervous system tumors especially in patients with high levels of tumoral cfDNA in the CSF. Further optimization of the collection procedure, experimental workflow and bioinformatic approach is required to also allow classification for patients with low tumoral fractions in the CSF.

Clinical implications of CSF-ctDNA positivity in newly diagnosed diffuse large B cell lymphoma.

The clinical implications of CSF-ctDNA positivity in newly diagnosed diffuse large B cell lymphoma (ND-DLBCL) remains largely unexplored. One hundred ND-DLBCL patients were consecutively enrolled as training cohort and another 26 ND-DLBCL patients were prospectively enrolled in validation cohort. CSF-ctDNA positivity (CSF(+)) was identified in 25 patients (25.0%) in the training cohort and 7 patients (26.9%) in the validation cohort, extremely higher than CNS involvement rate detected by conventional methods. Patients with mutations of CARD11, JAK2, ID3, and PLCG2 were more predominant with CSF(+) while FAT4 mutations were negatively correlated with CSF(+). The downregulation of PI3K-AKT signaling, focal adhesion, actin cytoskeleton, and tight junction pathways were enriched in CSF(+) ND-DLBCL. Furthermore, pretreatment CSF(+) was significantly associated with poor outcomes. Three risk factors, including high CSF protein level, high plasma ctDNA burden, and involvement of high-risk sites were used to predict the risk of CSF(+) in ND-DLBCL. The sensitivity and specificity of pretreatment CSF-ctDNA to predict CNS relapse were 100% and 77.3%. Taken together, we firstly present the prevalence and the genomic and transcriptomic landscape for CSF-ctDNA(+) DLBCL and highlight the importance of CSF-ctDNA as a noninvasive biomarker in detecting and monitoring of CSF infiltration and predicting CNS relapse in DLBCL.

Detection of tumor-derived cell-free DNA in cerebrospinal fluid using a clinically validated targeted sequencing panel for pediatric brain tumors.

PURPOSE: Clinical sequencing of tumor DNA is necessary to render an integrated diagnosis and select therapy for children with primary central nervous system (CNS) tumors, but neurosurgical biopsy is not without risk. In this study, we describe cell-free DNA (cfDNA) in blood and cerebrospinal fluid (CSF) as sources for "liquid biopsy" in pediatric brain tumors. METHODS: CSF samples were collected by lumbar puncture, ventriculostomy, or surgery from pediatric patients with CNS tumors. Following extraction, CSF-derived cfDNA was sequenced using UW-OncoPlex™, a clinically validated next-generation sequencing platform. CSF-derived cfDNA results and paired plasma and tumor samples concordance was also evaluated. RESULTS: Seventeen CSF samples were obtained from 15 pediatric patients with primary CNS tumors. Tumor types included medulloblastoma (n = 7), atypical teratoid/rhabdoid tumor (n = 2), diffuse midline glioma with H3 K27 alteration (n = 4), pilocytic astrocytoma (n = 1), and pleomorphic xanthoastrocytoma (n = 1). CSF-derived cfDNA was detected in 9/17 (53%) of samples, and sufficient for sequencing in 8/10 (80%) of extracted samples. All somatic mutations and copy-number variants were also detected in matched tumor tissue, and tumor-derived cfDNA was absent in plasma samples and controls. Tumor-derived cfDNA alterations were detected in the absence of cytological evidence of malignant cells in as little as 200 µl of CSF. Several clinically relevant alterations, including a KIAA1549::BRAF fusion were detected. CONCLUSIONS: Clinically relevant genomic alterations are detectable using CSF-derived cfDNA across a range of pediatric brain tumors. Next-generation sequencing platforms are capable of producing a high yield of DNA alterations with 100% concordance rate with tissue analysis.

Deciphering the causal relationship between plasma and cerebrospinal fluid metabolites and glioblastoma multiforme: a Mendelian Randomization study.

BACKGROUND: Glioblastoma Multiforme (GBM) is one of the most aggressive and fatal brain cancers. The study of metabolites could be crucial for understanding GBM's biology and reveal new treatment strategies. METHODS: The GWAS data for GBM were sourced from the FinnGen database. A total of 1400 plasma metabolites were collected from the GWAS Catalog dataset. The cerebrospinal fluid (CSF) metabolites data were collected from subsets of participants in the WADRC and WRAP studies. We utilized the inverse variance weighting (IVW) method as the primary tool to explore the causal relationship between metabolites in plasma and CSF and glioblastoma, ensuring the exclusion of instances with horizontal pleiotropy. Additionally, four supplementary analytical methods were applied to reinforce our findings. Aberrant results were identified and omitted based on the outcomes of the leave-one-out sensitivity analysis. Conclusively, a reverse Mendelian Randomization analysis was also conducted to further substantiate our results. RESULTS: The study identified 69 plasma metabolites associated with GBM. Of these, 40 metabolites demonstrated a significant positive causal relationship with GBM, while 29 exhibited a significant negative causal association. Notably, Trimethylamine N-oxide (TMAO) levels in plasma, not CSF, were found to be a significant exposure factor for GBM (OR = 3.1627, 95% CI = (1.6347, 6.1189), P = 0.0006). The study did not find a reverse causal relationship between GBM and plasma TMAO levels. CONCLUSIONS: This research has identified 69 plasma metabolites potentially associated with the incidence of GBM, among which TMAO stands out as a promising candidate for an early detectable biomarker for GBM.

Systematic Review of Cerebrospinal Fluid Biomarker Discovery in Neuro-Oncology: A Roadmap to Standardization and Clinical Application.

Effective diagnosis, prognostication, and management of CNS malignancies traditionally involves invasive brain biopsies that pose significant risk to the patient. Sampling and molecular profiling of cerebrospinal fluid (CSF) is a safer, rapid, and noninvasive alternative that offers a snapshot of the intracranial milieu while overcoming the challenge of sampling error that plagues conventional brain biopsy. Although numerous biomarkers have been identified, translational challenges remain, and standardization of protocols is necessary. Here, we systematically reviewed 141 studies (Medline, SCOPUS, and Biosis databases; between January 2000 and September 29, 2022) that molecularly profiled CSF from adults with brain malignancies including glioma, brain metastasis, and primary and secondary CNS lymphomas. We provide an overview of promising CSF biomarkers, propose CSF reporting guidelines, and discuss the various considerations that go into biomarker discovery, including the influence of blood-brain barrier disruption, cell of origin, and site of CSF acquisition (eg, lumbar and ventricular). We also performed a meta-analysis of proteomic data sets, identifying biomarkers in CNS malignancies and establishing a resource for the research community.

Diagnostic Value of sLR11 and sIL-2R in the Cerebrospinal Fluid for Malignant Central Nervous System Lymphoma.

Objective We previously reported that patients with acute leukemia and malignant lymphoma (ML) demonstrated significantly increased serum soluble LR11 (sLR11) levels compared to normal controls. Accurately diagnosing ML of the central nervous system (CNS ML) using cytology is frequently difficult. Therefore, we evaluated the use of cerebrospinal fluid (CSF) sLR11 and soluble interleukin-2 receptor (sIL-2R) as diagnostic and treatment response markers for CNS ML. Methods We retrospectively evaluated the CSF results for CNS ML using clinical data at our institution, and then analyzed the usefulness of sLR11 and sIL-2R in CSF for both the diagnosis and as surrogate markers that reflect the therapeutic effect. Patients We enrolled patients with CNS ML who received intrathecal anticancer drugs between 2017 and 2023. We analyzed the sLR11 and sIL-2R levels in CSF and cytological malignant grades. We studied 22 patients, including 17 with central nervous system (CNS) clinical conditions and five who received prevention treatment. Results The CSF sLR11 levels were significantly and positively correlated with CSF sIL-2R levels. The CSF sLR11 and sIL-2R levels in patients with CNS ML were significantly higher than those in the prevention group. A receiver operating characteristic (ROC) curve analysis showed the cut-off value of sLR11 for CNS invasion to be 21.7 ng/mL. Moreover, the chemotherapy-responder group demonstrated significantly decreased CSF sLR11 and sIL-2R levels after treatment. Conclusion CSF sLR11 and sIL-2R of CSF were found to be useful biomarkers for the diagnostic and treatment response evaluation in patients with CNS ML.

Single-cell atlas reveals the immunosuppressive microenvironment and Treg cells landscapes in recurrent Glioblastoma.

Patients diagnosed with glioblastoma (GBM) have the most aggressive tumor progression and lethal recurrence. Research on the immune microenvironment landscape of tumor and cerebrospinal fluid (CSF) is limited. At the single-cell level, we aim to reveal the recurrent immune microenvironment of GBM and the potential CSF biomarkers and compare tumor locations. We collected four clinical samples from two patients: malignant samples from one recurrent GBM patient and non-malignant samples from a patient with brain tumor. We performed single-cell RNA sequencing (scRNA-seq) to reveal the immune landscape of recurrent GBM and CSF. T cells were enriched in the malignant tumors, while Treg cells were predominately found in malignant CSF, which indicated an inhibitory microenvironment in recurrent GBM. Moreover, macrophages and neutrophils were significantly enriched in malignant CSF. This indicates that they an important role in GBM progression. S100A9, extensively expressed in malignant CSF, is a promising biomarker for GBM diagnosis and recurrence. Our study reveals GBM's recurrent immune microenvironment after chemoradiotherapy and compares malignant and non-malignant CSF samples. We provide novel targets and confirm the promise of liquid CSF biopsy for patients with GBM.

Intrathecal IgM synthesis as a diagnostic marker in patients with suspected CNS lymphoma.

For CNS lymphomas (CNSL), there is a high need for minimally invasive and easily obtainable diagnostic markers. Intrathecal IgM synthesis can easily be determined in routine CSF diagnostics. The aim of this study was to systematically investigate the diagnostic potential of intrathecal IgM synthesis in primary and secondary CNSL (PCNSL and SCNSL). In this retrospective study, patients with a biopsy-proven diagnosis of PCNSL or SCNSL were compared with patients with other neurological diseases in whom CNSL was initially the primary radiological differential diagnosis based on MRI. Sensitivity and specificity of intrathecal IgM synthesis were calculated using receiver operating characteristic curves. Seventy patients with CNSL were included (49 PCNSL and 21 SCNSL) and compared to 70 control patients. The sensitivity and specificity for the diagnosis of CNSL were 49% and 87%, respectively, for the entire patient population and 66% and 91% after selection for cases with tumor access to the CSF system and isolated intrathecal IgM synthesis. In cases with MRI-based radiological suspicion of CNSL, intrathecal IgM synthesis has good specificity but limited sensitivity. Because of its low-threshold availability, analysis of intrathecal IgM synthesis has the potential to lead to higher diagnostic accuracy, especially in resource-limited settings, and deserves further study.

Cerebrospinal Fluid cfDNA Sequencing for Classification of Central Nervous System Glioma.

PURPOSE: Primary central nervous system (CNS) gliomas can be classified by characteristic genetic alterations. In addition to solid tissue obtained via surgery or biopsy, cell-free DNA (cfDNA) from cerebrospinal fluid (CSF) is an alternative source of material for genomic analyses. EXPERIMENTAL DESIGN: We performed targeted next-generation sequencing of CSF cfDNA in a representative cohort of 85 patients presenting at two neurooncological centers with suspicion of primary or recurrent glioma. Copy-number variation (CNV) profiles, single-nucleotide variants (SNV), and small insertions/deletions (indel) were combined into a molecular-guided tumor classification. Comparison with the solid tumor was performed for 38 cases with matching solid tissue available. RESULTS: Cases were stratified into four groups: glioblastoma (n = 32), other glioma (n = 19), nonmalignant (n = 17), and nondiagnostic (n = 17). We introduced a molecular-guided tumor classification, which enabled identification of tumor entities and/or cancer-specific alterations in 75.0% (n = 24) of glioblastoma and 52.6% (n = 10) of other glioma cases. The overlap between CSF and matching solid tissue was highest for CNVs (26%-48%) and SNVs at predefined gene loci (44%), followed by SNVs/indels identified via uninformed variant calling (8%-14%). A molecular-guided tumor classification was possible for 23.5% (n = 4) of nondiagnostic cases. CONCLUSIONS: We developed a targeted sequencing workflow for CSF cfDNA as well as a strategy for interpretation and reporting of sequencing results based on a molecular-guided tumor classification in glioma. See related commentary by Abdullah, p. 2860.