Proteomic analysis of cerebrospinal fluid in pediatric acute lymphoblastic leukemia patients: a pilot study

Deep Proteome Analysis of Cerebrospinal Fluid from Pediatric Patients with Central Nervous System Cancer

The cerebrospinal fluid (CSF) is a key matrix for discovery of biomarkers relevant for prognosis and the development of therapeutic targets in pediatric central nervous system malignancies. However, the wide range of protein concentrations and age-related differences in children makes such discoveries challenging. In addition, pediatric CSF samples are often sparse and first prioritized for clinical purposes. The present work focused on optimizing each step of the proteome analysis workflow to extract the most detailed proteome information possible from the limited CSF resources available for research purposes. The strategy included applying sequential ultracentrifugation to enrich for extracellular vesicles (EV) in addition to analysis of a small volume of raw CSF, which allowed quantification of 1351 proteins (+55% relative to raw CSF) from 400 μL CSF. When including a spectral library, a total of 2103 proteins (+240%) could be quantified. The workflow was optimized for CSF input volume, tryptic digestion method, gradient length, mass spectrometry data acquisition method and database search strategy to quantify as many proteins a possible. The fully optimized workflow included protein aggregation capture (PAC) digestion, paired with data-independent acquisition (DIA, 21 min gradient) and allowed 2989 unique proteins to be quantified from only 400 μL CSF, which is a 340% increase in proteins compared to analysis of a tryptic digest of raw CSF.

Mass spectrometry-based proteomics of cerebrospinal fluid in pediatric central nervous system malignancies: a systematic review with meta-analysis of individual patient data

BACKGROUND

The cerebrospinal fluid (CSF) proteome could offer important insights into central nervous system (CNS) malignancies. To advance proteomic research in pediatric CNS cancer, the current study aims to (1) evaluate past mass spectrometry-based workflows and (2) synthesize previous CSF proteomic data, focusing on both qualitative summaries and quantitative re-analysis. MAIN: In our analysis of 11 studies investigating the CSF proteome in pediatric patients with acute lymphoblastic leukemia (ALL) or primary brain tumors, we observed significant methodological variability. This variability negatively affects comparative analysis of the included studies, as per GRADE criteria for quality of evidence. The qualitative summaries covered 161 patients and 134 non-tumor controls, while the application of validation cohort varied among the studies. The quantitative re-analysis comprised 15 B-ALL vs 6 "healthy" controls and 15 medulloblastoma patients vs 22 non-tumor controls. Certain CSF proteins were identified as potential indicators of specific malignancies or stages of neurotoxicity during chemotherapy, yet definitive conclusions were impeded by inconsistent data. There were no proteins with statistically significant differences when comparing cases versus controls that were corroborated across studies where quantitative reanalysis was feasible. From a gene ontology enrichment, we observed that age disparities between unmatched case and controls may mislead to protein correlations more indicative of age-related CNS developmental stages rather than neuro-oncological disease. Despite efforts to batch correct (HarmonizR) and impute missing values, merging of dataset proved unfeasible and thereby limited meaningful data integration across different studies.

CONCLUSION

Infrequent publications on rare pediatric cancer entities, which often involve small sample sizes, are inherently prone to result in heterogeneous studies-particularly when conducted within a rapidly evolving field like proteomics. As a result, obtaining clear evidence, such as CSF proteome biomarkers for CNS dissemination or early-stage neurotoxicity, is currently impractical. Our general recommendations comprise the need for standardized methodologies, collaborative efforts, and improved data sharing in pediatric CNS malignancy research. We specifically emphasize the possible importance of considering natural age-related variations in CSF due to different CNS development stages when matching cases and controls in future studies.

Proteomics in Childhood Acute Lymphoblastic Leukemia: Challenges and Opportunities

Acute lymphoblastic leukemia (ALL) is the most common cancer in children and one of the success stories in cancer therapeutics. Risk-directed therapy based on clinical, biologic and genetic features has played a significant role in this accomplishment. Despite the observed improvement in survival rates, leukemia remains one of the leading causes of cancer-related deaths. Implementation of next-generation genomic and transcriptomic sequencing tools has illustrated the genomic landscape of ALL. However, the underlying dynamic changes at protein level still remain a challenge. Proteomics is a cutting-edge technology aimed at deciphering the mechanisms, pathways, and the degree to which the proteome impacts leukemia subtypes. Advances in mass spectrometry enable high-throughput collection of global proteomic profiles, representing an opportunity to unveil new biological markers and druggable targets. The purpose of this narrative review article is to provide a comprehensive overview of studies that have utilized applications of proteomics in an attempt to gain insight into the pathogenesis and identification of biomarkers in childhood ALL.

Mass Spectrometry Contribution to Pediatric Cancers Research

For over four decades, mass spectrometry-based methods have provided a wealth of information relevant to various challenges in the field of cancers research. These challenges included identification and validation of novel biomarkers for various diseases, in particular for various forms of cancer. These biomarkers serve various objectives including monitoring patient response to the various forms of therapy, differentiating subgroups of the same type of cancer, and providing proteomic data to complement datasets generated by genomic, epigenetic, and transcriptomic methods. The same proteomic data can be used to provide prognostic information and could guide scientists and medics to new and innovative targeted therapies The past decade has seen a rapid emergence of epigenetics as a major contributor to carcinogenesis. This development has given a fresh momentum to MS-based proteomics, which demonstrated to be an unrivalled tool for the analyses of protein post-translational modifications associated with chromatin modifications. In particular, high-resolution mass spectrometry has been recently used for systematic quantification of chromatin modifications. Data generated by this approach are central in the search for new therapies for various forms of cancer and will help in attempts to decipher antitumor drug resistance. To appreciate the contribution of mass spectrometry-based proteomics to biomarkers discovery and to our understanding of mechanisms behind the initiation and progression of various forms of cancer, a number of recent investigations are discussed. These investigations also include results provided by two-dimensional gel electrophoresis combined with mass spectrometry.

Evaluation of aliphatic acid metabolism in bladder cancer with the goal of guiding therapeutic treatment

Urothelial bladder cancer (BLCA) is a common internal malignancy with a poor prognosis. The re-programming of lipid metabolism is necessary for cancer cell growth, proliferation, angiogenesis and invasion. However, the role of aliphatic acid metabolism genes in bladder cancer patients has not been explored. The samples’ gene expression and clinicopathological data were obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Univariate, multivariate, and LASSO Cox regression were used to develop a BLCA prognostic model. GSVA was used to assess function, whereas pRRophetic was used to assess chemotherapeutic drug sensitivity. The twelve-gene signature may define the tumor immune milieu, according to the risk score model. We compared the expression of aliphatic acid metabolism genes in malignant and non-cancerous tissues and chose 90 with a false discovery rate of 0.05 for The Cancer Genome Atlas cohort. The prognostic risk score model can effectively predict BLCA OS. A nomogram including age, clinical T stage, gender, grade, pathological stage, and clinical M stage was developed as an independent BLCA prognostic predictor. The halfmaximal inhibitory concentration (IC50) was used to assess chemotherapeutic medication response. Sorafenib and Pyrimethamine were used to treat patients with low risk scores more sensitively than patients with high risk scores. Immunotherapy candidates with CMS1 exhibited higher risk ratings. The aliphatic acid prognostic risk score model can assess metabolic trends. Clinical stage and molecular subtype may be used to categorize individuals using the risk score.With this new paradigm, future cancer treatment and immunotherapy may be tailored to the patient’s exact requirements.

Potential Roles of Acute Phase Proteins in Cancer: Why Do Cancer Cells Produce or Take Up Exogenous Acute Phase Protein Alpha1-Antitrypsin?

An association between acute-phase proteins (APPs) and cancer has long been established and there are numerous reports correlating altered levels and/or molecular forms of APPs with different types of cancers. Many authors have shown a positive correlation between high levels of APPs, like alpha1-antitrypsin (AAT), and unfavorable clinical outcome in cancers. Conversely, others proposed that high levels of APPs are probably just a part of nonspecific inflammatory response to cancer development. However, this might not be always true, because many cancerous cells produce or take up exogenous APPs. What is the biological significance of this and what benefit do cancer cells have from these proteins remains largely unknown. Recent data revealed that some APPs, including AAT, are able to enhance cancer cell resistance against anticancer drug-induced apoptosis and autophagy. In this review, we specifically discuss our own findings and controversies in the literature regarding the role of AAT in cancer.

Cerebrospinal Fluid Biomarkers in Childhood Leukemias

Involvement of the central nervous system (CNS) in childhood leukemias remains a major cause of treatment failures. Analysis of the cerebrospinal fluid constitutes the most important diagnostic pillar in the detection of CNS leukemia and relies primarily on cytological and flow-cytometry studies. With increasing survival rates, it has become clear that treatments for pediatric leukemias pose a toll on the developing brain, as they may cause acute toxicities and persistent neurocognitive deficits. Preclinical research has demonstrated that established and newer therapies can injure and even destroy neuronal and glial cells in the brain. Both passive and active cell death forms can result from DNA damage, oxidative stress, cytokine release, and acceleration of cell aging. In addition, chemotherapy agents may impair neurogenesis as well as the function, formation, and plasticity of synapses. Clinical studies show that neurocognitive toxicity of chemotherapy is greatest in younger children. This raises concerns that, in addition to injury, chemotherapy may also disrupt crucial developmental events resulting in impairment of the formation and efficiency of neuronal networks. This review presents an overview of studies demonstrating that cerebrospinal fluid biomarkers can be utilized in tracing both CNS disease and neurotoxicity of administered treatments in childhood leukemias.

Expression of Viral microRNAs in Serum and White Blood Cells of Cows Exposed to Bovine Leukemia Virus

Bovine leukemia virus (BLV) affects the health and productivity of cattle. The virus causes abnormal immune function and immunosuppression. MicroRNAs (miRNAs) are involved in gene expression, having been associated with stress and immune response, tumor growth, and viral infection. The objective of this study was to determine the expression of circulating miRNAs produced by BLV in animals exposed to the virus. Sera from 14 animals were collected to establish IgG reactivity to BLV by ELISA, where seven animals were seropositive and seven were seronegative for BLV exposure. White blood cells (WBC) from each animal were also collected and miRNAs were identified by sequencing from sera and WBC. The seropositive group had higher counts of BLV miRNAs when compared to seronegative group in sera and WBC. Blv-miR-1-3p, blv-miR-B2-5p, blv-miR-B4-3p, and blv-miR-B5-5p were statistically significant (P < 0.00001) in serum with an average of 7 log2 fold difference between seropositive and seronegative groups. Blv-miR-B1-3p, blv-miR-B1-5p, blv-miR-B3, blv-miR-B4-3p, blv-miR-B4-5p, blv-miR-B5-5p were statistically significant (P < 1.08e⁻⁹) in WBC with an average of 7 log2 fold difference between the seropositive and the seronegative groups. Blv-miR-B2-3p and blv-miR-B2-5p were also statistically significant in WBC (P < 2.79e-17), with an average of 27 log2 fold difference between the seropositive and the seronegative groups. There were 18 genes identified as being potential targets for blv-miR-B1-5p, and 3 genes for blv-miR-B4-5p. Gene ontology analysis indicated that the target genes are mainly involved in the response to stress and in the immune system process. Several of the identified genes have been associated with leukemia development in humans and cattle. Differential expression of genes targeted by BLV miRNAs should be evaluated to determine their effect in BLV replication.

Human CNS barrier-forming organoids with cerebrospinal fluid production

Cerebrospinal fluid (CSF) is a vital liquid, providing nutrients and signaling molecules and clearing out toxic by-products from the brain. The CSF is produced by the choroid plexus (ChP), a protective epithelial barrier that also prevents free entry of toxic molecules or drugs from the blood. Here, we establish human ChP organoids with a selective barrier and CSF-like fluid secretion in self-contained compartments. We show that this in vitro barrier exhibits the same selectivity to small molecules as the ChP in vivo and that ChP-CSF organoids can predict central nervous system (CNS) permeability of new compounds. The transcriptomic and proteomic signatures of ChP-CSF organoids reveal a high degree of similarity to the ChP in vivo. Finally, the intersection of single-cell transcriptomics and proteomic analysis uncovers key human CSF components produced by previously unidentified specialized epithelial subtypes.