Search Results (439)

Chemotherapy-induced neurotoxicity is a major dose-limiting complication of systemic anticancer therapy that adversely affects neurological function, treatment continuity, and long-term quality of life among cancer survivors. Chemotherapy-induced peripheral neuropathy (CIPN) is the most common manifestation, whereas chemotherapy-related cognitive impairment (CRCI) and selected immune-mediated neurological toxicities increasingly contribute to survivorship-related morbidity. Although these immune-mediated syndromes are distinct from conventional chemotherapy-induced neurotoxicity, they are included because they share several downstream pathogenic mechanisms relevant to biomarker discovery and neuroprotective strategies. This structured narrative review critically synthesizes current evidence on the molecular mechanisms, clinical manifestations, biomarkers, and emerging neuroprotective strategies underlying chemotherapy-induced neurotoxicity. A comprehensive PubMed/MEDLINE search was performed, with emphasis on studies published between 2014 and 2026. Evidence from systematic reviews, meta-analyses, clinical guidelines, randomized controlled trials, prospective clinical studies, and high-quality translational research was critically evaluated. Current evidence indicates that chemotherapy-induced neurotoxicity arises through interconnected mechanisms involving oxidative stress, mitochondrial dysfunction, neuroinflammation, calcium dysregulation, blood–brain barrier disruption, and SARM1-mediated programmed axonal degeneration. Among emerging biomarkers, neurofilament light chain (NfL) demonstrates the greatest translational potential for early detection and monitoring, while inflammatory cytokines, circulating microRNAs, pharmacogenomic markers, cerebrospinal fluid biomarkers, and advanced neuroimaging may improve individualized risk stratification. Although duloxetine remains the only guideline-recommended pharmacological treatment for established painful CIPN, mechanism-based therapies targeting mitochondrial dysfunction, neuroinflammation, oxidative stress, and SARM1 signaling, together with structured exercise and biomarker-guided precision medicine, represent promising translational approaches. However, clinical implementation remains limited by incomplete biomarker validation, heterogeneous study methodologies, and the absence of effective disease-modifying neuroprotective therapies, underscoring the need for large biomarker-guided multicenter clinical trials. Full article

Background/Objectives: Glioblastoma (GBM) is the most lethal primary brain malignancy in adults, with a median overall survival of approximately 15 months. Temozolomide (TMZ) resistance develops in virtually all patients, and no second-line regimen has improved outcomes over the past two decades. The DNA methyltransferase inhibitor decitabine (DAC) has attracted interest as a chemosensitizer, but whether it directly reverses the TMZ-resistance transcriptome or operates through distinct, complementary mechanisms has not been tested at multi-omics resolution. Methods: We performed an integrative six-layer multi-omics analysis across five public GEO datasets (bulk RNA-seq, EPIC 850K methylation, and 21,676 single cells) re-purposed from studies conducted for unrelated aims, formally tested DAC-mediated reversal of the TMZ-resistance transcriptome across 11,707 genes, mapped pharmacogenomic targets with DGIdb v5, and built an exploratory, hypothesis-generating 11-gene prognostic model internally validated in TCGA-GBM (n = 166) and externally tested in the independent CPTAC-GBM cohort (n = 96). Results: DAC reprogrammed transcription across 1114–1882 differentially expressed genes per cohort and reactivated 146 direct epigenetic targets, identifying INPP5D/SHIP1 as the top-ranked direct epigenetic-reactivation target. Genome-wide reversal analysis across 11,707 co-detected genes showed a negligible effect (Spearman ρ = 0.073), but single-cell analysis revealed significant per-cell attenuation of MES-like and stem-like programs (Δ = −0.071 and −0.135, respectively; both p < 0.001). The 11-gene risk model achieved a Harrell’s C-index of 0.706 (apparent); after correcting for the two-stage gene selection with a full-pipeline bootstrap, the optimism-corrected C-index was 0.63, and external validation in an independent cohort (CPTAC-GBM, n = 96) showed only near-chance discrimination (C-index 0.55), indicating that the signature does not generalize and is exploratory. Pharmacogenomic mapping yielded 734 unique therapeutic agents (230 FDA-approved) across 69 druggable targets after excluding AR. Most of these agents are not GBM-directed, so this catalog-level mapping is hypothesis-generating rather than a set of therapeutic recommendations. Conclusions: DAC does not broadly reverse the TMZ-resistant transcriptome but acts through three complementary mechanisms: epigenetic reactivation of INPP5D/SHIP1, cancer-testis-antigen and type I interferon induction, and per-cell attenuation of mesenchymal–stem-like transcriptional intensity, supporting hypotheses for rationally designed DAC-based combination therapy in TMZ-resistant GBM. Full article

Quantum machine learning (QML) has emerged as a promising approach for analyzing the complex, high-dimensional data encountered in oncology, yet research in this area remains fragmented. This systematic literature review synthesizes current applications of QML in cancer care. Following PRISMA guidelines, six databases were searched for peer-reviewed English-language studies published between 2020 and 2026. Of the 212 records identified, 49 studies met the inclusion criteria after screening and quality assessment. The findings show that QML research is dominated by classification and detection tasks, while segmentation is beginning to emerge. Breast cancer and brain tumors are the most frequently investigated domains. Hybrid quantum-classical models, particularly quantum kernel methods, quantum neural networks, and quantum convolutional neural networks, are the predominant approaches. The main barriers to adoption are hardware limitations, including quantum noise, limited qubit availability, and reliance on simulators. Overall, QML in oncology remains in its early stages of development, with limited clinical validation, insufficient model interpretability, and little evidence of a clear quantum advantage. Future research should prioritize evaluation on real quantum hardware, larger and more diverse clinical datasets, standardized benchmarking against classical methods, and closer collaboration between computer scientists and oncology experts to facilitate clinical translation. Full article

Brain metastases in hormone receptor-positive metastatic breast cancer remain incompletely characterized at the molecular level. We report isolated central nervous system progression in a 60-year-old woman with hormone receptor-positive breast cancer initially diagnosed at the age of 38 and metastatic recurrence diagnosed at the age of 55. After approximately five years of extracranial disease control with letrozole plus palbociclib, she developed multiple brain metastases, including a large cerebellar lesion requiring surgical resection. Molecular profiling of the resected lesion identified ESR1 Y537S and ERBB2 Y772_A775dup, whereas postoperative plasma circulating tumor DNA analyzed using a sensitive next-generation sequencing assay showed no detectable somatic alteration. Extracranial disease remained in complete metabolic response. This tissue–plasma discordance is compatible with spatial genomic heterogeneity but may also reflect a low circulating tumor fraction, postoperative reduction in tumor burden, and limited release of tumor-derived DNA from CNS lesions into the systemic circulation. This case highlights the limitations of plasma circulating tumor DNA for evaluating CNS-limited progression and supports direct molecular profiling of brain metastases when tissue is available. Full article

Chemotherapy is a treatment designed to contain or eradicate neoplastic cells; however, patients may experience various treatment-related adverse effects. Chemotherapy-related cognitive impairment (CRCI), clinically referred to as “chemobrain,” is a frequent complication with a duration ranging from months to years, affecting between 17% and 70% of cancer patients. These cognitive deficits not only impair social, educational, and occupational functioning but may also impact survival outcomes, possibly by interfering with medication adherence and health-related behaviors. Emerging evidence has converged on an integrative cascade in which chemotherapy-induced systemic inflammation, intestinal dysbiosis, blood–brain barrier disruption, microglial/astroglial activation, and impaired hippocampal neurogenesis act in sequence rather than as independent pathways. Underlying pathophysiological mechanisms include neuroinflammation, reduced neurogenesis, loss of dendritic spines, oxidative stress, hormonal changes, epigenetic modifications, and mitochondrial dysfunction. In contrast, repair mechanisms involve complex glial responses, particularly those of astrocytes and microglia. Emerging studies suggest a link between changes in the microbiome and cognitive decline, demonstrating the importance of bidirectional communication in the gut–brain axis. Current research seeks to determine appropriate tests to identify chemobrain. Therefore, several biomarkers, such as GFAP, S100β, and isoprostanes, have been proposed to assess chemobrain, alongside screening tools such as MoCA, MMSE, and CAB-CF, to evaluate cognitive impairment and enable early detection. Pharmacological candidates—including lithium, fluoxetine, methylphenidate, modafinil, metformin, agomelatine, and melatonin—as well as nutritional and lifestyle interventions such as physical exercise, omega-3 fatty acids, curcumin, probiotics, and traditional Chinese medicine formulations—have been investigated, predominantly in animal models. These remain candidate, not validated, therapies; clinical evidence in CRCI populations is limited, heterogeneous, or absent, and well-powered randomized controlled trials are required before any recommendation can be issued. However, optimal strategies for symptom improvement remain unclear, as various approaches have yielded mixed outcomes. This review provides a comprehensive overview of chemobrain, focusing on its molecular mechanisms, interactions with the gut–brain axis, and potential therapeutic targets to improve the quality of life for cancer survivors. Full article

Unc-51-like kinase 3 (ULK3) is a key member of the ULK serine/threonine kinase family. Aberrant ULK3 expression has been increasingly linked to tumorigenesis and malignant progression in multiple cancer types. However, the precise role of ULK3 in tumor initiation and progression remains incompletely understood. Leveraging integrated multi-omics data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) project, and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), we systematically characterized the expression of ULK3 at both the transcript and protein levels across 33 cancer types. We also evaluated genomic alterations, prognostic significance, alternative splicing, pathway enrichment, tumor stemness, immune infiltration, and immunotherapy-related biomarkers. In parallel, we investigated the function of ULK3 in prostate cancer PC-3 cells using cellular localization analysis, wound-healing assays, and MTT assays. We further applied Connectivity Map (CMap) screening and molecular docking to identify candidate ULK3 activators. ULK3 was significantly upregulated in 13 cancer types, including Bladder Urothelial Carcinoma, Breast Invasive Carcinoma, and Lung Adenocarcinoma. In contrast, ULK3 was downregulated in Cholangiocarcinoma and Head and Neck Squamous Cell Carcinoma. High ULK3 expression was associated with poor overall survival in Adrenocortical Carcinoma, Kidney Renal Clear Cell Carcinoma, and Skin Cutaneous Melanoma. Copy number amplification contributed to ULK3 overexpression. A recurrent A206V missense mutation was detected in the protein kinase (Pkinase) domain. Genes co-expressed with ULK3 were enriched in RNA splicing, methylation, oxidative phosphorylation, and energy metabolism. ULK3 expression showed positive correlations with tumor stemness indices and m1A/m5C/m6A RNA modification regulators. From an immunological perspective, high ULK3 expression was associated with lower Immune Score, increased M2 macrophage infiltration, and co-expression of PD-L1, CTLA4, and LAG3 in most cancers. ULK3 expression was also correlated with Tumor Mutational Burden in Kidney Renal Clear Cell Carcinoma and Rectum Adenocarcinoma. In addition, ULK3 expression was associated with Microsatellite Instability in Brain Lower Grade Glioma, Lung Adenocarcinoma, and Uterine Corpus Endometrial Carcinoma. ULK3 overexpression promoted proliferation and migration in PC-3 cells. Cephaeline was screened as a putative ULK3 activator. Overall, ULK3 expression and amplification were associated with poor clinical outcomes, tumor stemness, immunosuppression, and RNA dysregulation. These findings highlight the potential value of ULK3 as a pan-cancer diagnostic and prognostic biomarker and as a predictor of immunotherapy response, particularly in prostate cancer. Full article

In this study, a new series of (E)-4-((2-(2-(4-amino-3-methyl-5-oxo-4,5-dihydro-1H-1,2,4-triazol-1-yl)acetyl)hydrazono)methyl)phenyl 4-halogenobenzenesulfonates (3a–3d), where 3a = F, 3b = Cl, 3c = Br, and 3d = I, were successfully synthesized via a straightforward synthetic route. The structures of the obtained compounds were fully characterized and confirmed by spectroscopic techniques, including FT-IR, ¹H NMR, and ¹³C NMR, as well as LC-MS/MS analysis. 1,2,4-triazole-based hydrazone derivatives (3a–3d) were investigated using IR and NMR spectroscopy and DFT calculations. Intermolecular interactions, HOMO-LUMO, dipole moment, polarization, first-order hyperpolarizability, and molecular electrostatic potential studies on the molecules were examined. The HOMO and LUMO energy gap study supports the charge transfer probability in the molecules. These were conducted to investigate the reactivity and stability of heterocyclic molecules in bioactivity analysis. Electron density mapping within the molecular electrostatic potential plot and electrostatic potential representation within the iso-surface plot evaluated the concept of charge distribution in the molecule as nucleophilic reactions and electrophilic regions. The predicted nonlinear optical (NLO) properties of the molecules are much greater than those of urea. The results obtained from these investigations collectively provide evidence that the molecules possess nonlinear optical applications. Novel triazole–hydrazone-functionalized aryl sulfonate derivatives (3a–3d) were evaluated for their anticancer potential against a panel of brain and non-brain cancer cell lines. Compound 3b exhibited the most favorable overall biological profile, displaying potent activity against SH-SY5Y neuroblastoma (GI = 7.59 μM) and U87MG glioblastoma cells (GI = 13.85 μM), together with the lowest toxicity toward normal FL fibroblasts (GI = 62.02 μM). Compounds 3c and 3d demonstrated remarkable potency against IDHmut-U87 glioma cells (GI = 3.87 and 3.27 μM, respectively), although their selectivity toward cancer cells was limited. DNA degradation studies revealed substantial fragmentation, particularly in C6 and SH-SY5Y cells, while migration assays indicated reduced cellular motility. Molecular docking studies identified compound 3b as the strongest PI3Kα binder, supporting a possible. In addition, the antimicrobial activities of compounds 3a–3d were evaluated against selected Gram-positive and Gram-negative bacteria as well as Candida species using the broth microdilution method. The compounds exhibited measurable antimicrobial effects with MIC values ranging from 156 to 625 µg/mL, showing moderate growth inhibition against the tested microorganisms. Although the observed activity was lower than that of the reference antimicrobial agents, the results indicate that these triazole–hydrazone derivatives possess a detectable level of antimicrobial activity and provide a basis for further structural optimization. Collectively, the results suggest that compound 3b represents the most promising lead structure due to its balanced combination of potency, selectivity, and predicted target engagement. Molecular docking was performed to evaluate the binding potential of newly synthesized triazole derivatives (3a–3d) against PI3Kα. The docking protocol was validated by re-docking alpelisib, yielding an RMSD of 0.64 Å. Among the tested compounds, 3b showed the most favorable binding energy (−9.94 kcal/mol) and estimated Ki value (52.13 nM), consistent with its superior in vitro activity. Its interactions with key PI3Kα residues, including Val851, Ser854, Met922, and Asp933, support a stable binding mode within the ATP-binding pocket. In silico ADME and toxicity analyses suggested acceptable drug-likeness characteristics, absence of major hepatotoxic, mutagenic, and carcinogenic liabilities, and moderate predicted acute toxicity profiles. These findings suggest that 3b is the most promising derivative for further validation. Full article

Background: Comprehensive genomic profiling (CGP) via next-generation sequencing (NGS) is pivotal for precision oncology, yet many laboratories face challenges with incomplete genomic coverage, complex bioinformatics workflows, and limited integration of key biomarkers. Methods: We evaluated the analytical performance and clinical utility of a CGP assay using 119 tumor samples representing 18 types of cancer, previously analyzed with an orthogonal NGS panel. Concordance was assessed across 81 genes, covering 176 single-nucleotide variants (SNVs), eight copy number variations (CNVs), four deletions, one duplication, and four gene fusions. Limit of detection (LOD) studies employed AcroMetrix Mutant Hotspot Control and SeraSeq Lung and Brain CNV Mix. Microsatellite instability (MSI) and tumor mutational burden (TMB) were quantified. Inter- and intra-run reproducibility were evaluated to assess precision. Results: The CGP assay demonstrated high analytical performance, with >99% sensitivity, 100% specificity, and complete accuracy for variant detection. LOD studies revealed robust detection of SNVs at ≤5% variant allele frequencies (VAF) and CNVs at three copies. MSI and TMB results were consistent with clinical expectations, showing minimal bias compared to the orthogonal panel. Inter- and intra-run testing confirmed 100% reproducibility, indicating strong assay precision. Post-sequencing variant reporting was streamlined using the iCare platform, enabling direct FASTQ-to-report generation without intermediate bioinformatic steps. Conclusions: These findings support the present assay’s clinical utility in personalized oncology assessment. Full article

Obesity is a major risk factor for colorectal cancer (CRC) and is increasingly recognized as a contributor to cancer-related cognitive impairment; however, the mechanistic pathways linking metabolic dysfunction, tumor progression, and brain dysfunction remain incompletely defined. Emerging evidence indicates that obesity-induced gut microbial dysbiosis and intestinal barrier disruption may serve as a biologically plausible mechanism connecting these processes via the gut–brain axis although direct clinical causality remains to be firmly established. In obesity, alterations in gut microbiota composition characterized by depletion of barrier-protective taxa and enrichment of pro-inflammatory and genotoxic pathobionts compromise epithelial tight-junction integrity and promote metabolic endotoxemia. The translocation of microbial products, including lipopolysaccharide, sustains chronic systemic inflammation, accelerates CRC progression, and remodels the tumor microenvironment. Notably, these peripheral inflammatory signals extend beyond the intestine and tumor, disrupting blood–brain barrier integrity, activating microglia and astrocytes, and impairing synaptic plasticity within hippocampal and frontal networks. Clinically, these processes manifest as cancer-related cognitive impairment (CRCI), with predominant deficits in attention, processing speed, and working memory, which are often detectable around the time of diagnosis and independent of chemotherapy exposure. This review synthesizes in vivo, in vitro, and human evidence into a proposed theoretical “two-barrier failure” model of obesity-associated CRC and cognitive dysfunction. In addition to mechanistic synthesis, we discuss barrier-centered therapeutic strategies, including targeted probiotics, postbiotics, SCFA supplementation, obesity management through dietary and weight-loss interventions, and potential pharmacological approaches to epithelial and neurovascular barrier protection. We also outline testable clinical trial designs for evaluating these interventions in obesity-associated CRC. Full article

Background: Oligometastatic non-small cell lung cancer (OMD NSCLC) represents a distinct clinical state with limited metastatic spread, where local ablative therapies (LAT) combined with systemic treatment may improve outcomes. Accurate staging and prognostic assessment are critical, with ¹⁸F-FDG PET/CT emerging as a valuable tool for detecting metabolically active tumor burden. Results: We retrospectively analyzed 38 patients with synchronous OMD NSCLC who received radiotherapy. All patients underwent ¹⁸F-PET/CT and brain imaging for staging. Semi-quantitative ¹⁸F-PET/CT parameters, including metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of primary tumor and metastatic lesions, were measured and associated with progression-free survival (PFS) and overall survival (OS) using Cox proportional hazard models. The median PFS and OS were 8.28 and 21.62 months, respectively. Higher MTV and TLG values of metastases were significantly associated with shorter PFS and OS (p < 0.01). In multivariable analysis, TLG of metastases above the median remained an independent predictor of worse PFS (HR = 2.78, p = 0.031) and OS (HR = 3.12, p = 0.024), alongside clinical factors such as ECOG performance status 2 and having multiple metastases. The metabolic parameters of the primary tumor did not predict survival outcomes. Conclusions:¹⁸F-PET/CT-derived metabolic parameters, particularly the TLG of metastatic lesions, may provide significant prognostic information in oligometastatic NSCLC beyond clinical variables. These findings may support the integration of ¹⁸F-PET/CT metrics for future trials involving patients treated with LAT in oligometastatic NSCLC. Full article

Background: The incidence of cancer-associated thromboembolism has been extensively investigated, but mostly in heterogeneous cancer populations. Prognostic risk assessment is crucial in pulmonary embolism, but the accuracy of the commonly used tools remains uncertain in patients with cancer. Methods: We retrospectively included outpatients with consecutive lung cancer attending the Pulmonary Unit in Pisa from July 2019 to June 2021. The study population was the subgroup of patients who developed at least one episode of pulmonary embolism. For all patients, clinical data within 72 h of pulmonary embolism diagnosis, Khorana Risk Score, and overall survival time were collected. Results: A total of 512 patients with lung cancer attended the clinic; 40 patients developed pulmonary embolism (cumulative incidence of 7.81%). Eight patients (20%) died within a month, and twenty-two patients (55%) died within 6 months. Troponin, N-terminal pro-brain-type natriuretic peptide and shock index were significantly different between survivors and non-survivors (p < 0.05). Pulmonary artery diameter and the right to left ventricle index were not significantly different between survivors and non-survivors. Patients’ survival significantly decreased with the increase in Khorana Risk Score. Conclusions: Compared to previous studies, a higher incidence of pulmonary embolism in lung cancer was detected by our study. The prognosis of patients with lung cancer with pulmonary embolism seemed to be influenced more by the natural history of cancer than by the severity of pulmonary embolism. Khorana Risk Score might be considered as a prognostic tool in patients with lung cancer and may be used in the prognostic work-up for lung cancer-associated thromboembolism after a prospective validation. Full article

Pediatric brain and other central nervous system (CNS) tumors remain a leading cause of cancer-related death in children, while contemporary management increasingly depends on molecular classification, risk stratification, and longitudinal disease assessment. Yet tissue-based profiling has major limitations in pediatric neuro-oncology, particularly for deep-seated, eloquent, or surgically hazardous tumors and when repeat sampling is impractical. For primary CNS tumors, cerebrospinal fluid is generally more informative than plasma because it is anatomically closer to the tumor and more enriched for tumor-derived material. This narrative review summarizes current and emerging applications of cerebrospinal fluid in pediatric neuro-oncology, from conventional staging to molecular diagnosis, methylation-based classification, measurable residual disease detection, pharmacodynamic monitoring, and relapse surveillance. We discuss the biological rationale for cerebrospinal fluid analysis, major pre-analytical and technical determinants of assay performance, and the strengths and limitations of key analyte classes, including cytology, circulating tumor cells, cell-free DNA, RNA, extracellular vesicles, proteins, and metabolites. We also summarize how these approaches are being applied across major pediatric central nervous system tumor entities. Cerebrospinal fluid liquid biopsy is unlikely to replace tissue or imaging, but is increasingly positioned to complement both in precision pediatric neuro-oncology. Full article

Brain tumors in older adults are difficult to diagnose and manage due to nonspecific symptoms, overlapping with neurodegenerative diseases such as dementia, and significant tumor heterogeneity. Although molecular markers such as IDH1/2 mutations, MGMT promoter methylation, TERT alterations, and 1p/19q co-deletion have improved glioma classification and prognostic assessment, current care still relies on invasive tissue biopsies, which limit longitudinal monitoring and may not fully capture tumor complexity because of sampling bias, assay variability, and limited accessibility. Liquid biopsy offers a promising alternative that enables the detection of tumor-derived DNA, RNA, proteins, and extracellular vesicles, supporting earlier diagnosis and real-time monitoring of disease progression and treatment response. However, liquid biopsy for brain tumors is not yet clinically definitive due to low biomarker abundance, lack of standardization, and limited validation, and therefore, it cannot replace tissue diagnosis. Ongoing research focuses on multi-analyte biomarker panels, improved assay standardization, and integration with imaging and tissue-based data. In parallel, artificial intelligence and machine learning are advancing the field by integrating multi-omics and radiomic data to enhance detection, classify tumors, and predict key molecular alterations, supporting the emerging framework of radiogenomics. Together, these developments are driving a shift toward more precise and dynamic approaches to brain tumor diagnosis and management, with relevance for improving outcomes in older adults with brain cancer. Full article

Recent research suggests a link between EBV and brain cancer, especially in high-grade gliomas, but its role has not been sufficiently elucidated. Therefore, we evaluated its occurrence in brain cancer. For this purpose, the EBV DNA and LMP-1 in tumor tissue, the level of viral load in the cerebrospinal fluid (CSF), and the serological status of patients were analyzed. We detected EBV DNA in 28.9% (42/145) of glioma samples, among which 28 were isolated from glioblastomas (GBs) and 14 from other gliomas. LMP-1 was detected in 26 (92.8%) GB samples and 5 (35.7%) samples from other gliomas. The EBV DNA load in the CSF was significantly higher in GB compared to other gliomas; anti-EBNA1, anti-EBVCA, anti-EA, and anti-Zta antibodies were detected in the serum of GB patients; and their concentration was higher in GB patients. Further research is needed to determine whether and to what extent EBV contributes to glioma development. Elucidating the role of latent EBV genes synthesized in glioblastoma is important for understanding the role of viral infection in cancer development and progression in this hitherto poorly studied area. Full article

Background: Evaluation of gene-level copy number variants (CNVs) for diagnosis and therapeutic decision making has become standard of care with next-generation sequencing (NGS), immunohistochemistry (IHC), and/or fluorescence in situ hybridization (FISH) being used to detect gene amplifications/deletions in tumor tissue. In contrast to most solid tumors, CNS cancers are challenging to evaluate by resection and/or biopsy due to the associated risks with invasive brain surgery that can also result in death or associated morbidity and therefore alternate methods are required.Methods: This study presents the analytical validation of using quantitative PCR (qPCR) to detect gene CNVs directly from cerebrospinal fluid (CSF)-derived DNA and from the Ascent^TM low-pass whole genome sequencing (LP-WGS) libraries, demonstrating concordance with the gold standard of NGS/IHC/FISH used in tumor tissue. Results: The analytical sensitivity of qPCR to detect gene amplification calls for ERBB2 (erb-b2 receptor tyrosine kinase 2) was demonstrated to be 100% and that of EGFR (epidermal growth factor receptor) was 83%, with specificities of 96% and 100%, respectively. The analytical sensitivity of qPCR to detect gene deletions for CDKN2A/2B (cyclin-dependent kinase inhibitor 2A/2B) was 60% and that for MTAP (methylthioadenosine phosphorylase) was 100% with a specificity of 100% for all three genes. Ascent^TM was demonstrated to have a higher sensitivity (100%) when compared to qPCR for the same genes evaluated and demonstrated 100% positive agreement and 100% negative agreement with known CNV status. Conclusions: The results demonstrate that given the paucity of cells in CSF limiting the use of IHC and FISH, qPCR and Ascent^TM provide highly sensitive, novel, minimally invasive methods for the evaluation of gene copy number (CN) status to inform the diagnosis and management of CNS cancers. Full article