Proteomics and metabolomics approach in adult and pediatric glioma diagnostics

TMT-Based Quantitative Proteomic Profiling of Human Esophageal Cancer Cells Reveals the Potential Mechanism and Potential Therapeutic Targets Associated With Radioresistance

PURPOSE

The recurrence of esophageal squamous cell carcinoma (ESCC) in radiation therapy treatment presents a complex challenge due to its resistance to radiation. However, the mechanism underlying the development of radioresistance in ESCC remains unclear. In this study, we aim to uncover the mechanisms underlying radioresistance in ESCC cells and identify potential targets for radiosensitization.

METHODS

We established two radio-resistant cell lines, TE-1R and KYSE-150R, from the parental ESCC cell lines TE-1 and KYSE-150 through fractionated irradiation. A TMT-based quantitative proteomic profiling approach was applied to identify changes in protein expression patterns. Cell Counting Kit-8, colony formation, γH2AX foci immunofluorescence and comet assays were utilized to validate our findings. The downstream effectors of the DNA repair pathway were confirmed using an HR/NHEJ reporter assay and Western blot analysis. Furthermore, we evaluated the expression of potential targets in ESCC tissues through immunohistochemistry combined with mass spectrometry.

RESULTS

Over 2,000 proteins were quantitatively identified in the ESCC cell lysates. A comparison with radio-sensitive cells revealed 61 up-regulated and 14 down-regulated proteins in the radio-resistant cells. Additionally, radiation treatment induced 24 up-regulated and 12 down-regulated proteins in the radio-sensitive ESCC cells. Among the differentially expressed proteins, S100 calcium binding protein A6 (S100A6), glutamine gamma-glutamyltransferase 2 (TGM2), glycogen phosphorylase, brain form (PYGB), and Thymosin Beta 10 (TMSB10) were selected for further validation studies as they were found to be over-expressed in the accumulated radio-resistant ESCC cells and radio-resistant cells. Importantly, high S100A6 expression showed a positive correlation with cancer recurrence in ESCC patients. Our results suggest that several key proteins, including S100A6, TGM2, and PYGB, play a role in the development of radioresistance in ESCC.

CONCLUSIONS

Our results revealed that several proteins including Protein S100-A6 (S100A6), Protein-glutamine gamma-glutamyltransferase 2 (TGM2), Glycogen phosphorylase, brain form (PYGB) were involved in radio-resistance development. These proteins could potentially serve as biomarkers for ESCC radio-resistance and as therapeutic targets to treat radio-resistant ESCC cells.

Blood and cerebrospinal fluid biomarkers in neuro-oncology

PURPOSE OF REVIEW

The purpose of this review is to discuss the value of blood and CSF biomarkers in primary CNS tumors.

RECENT FINDINGS

Several analytes can be assessed with liquid biopsy techniques, including circulating tumor cells, circulating cell-free tumor DNA, circulating cell-free RNA, circulating proteins and metabolites, extracellular vesicles and tumor-educated platelets. Among diffuse gliomas of the adult, ctDNA in blood or CSF has represented the most used analyte, with the detection of molecular alterations such as MGMT promoter, PTEN, EGFRVIII, TERT promoter mutation and IDH R132H mutation. In general, CSF is enriched for ctDNA as compared with plasma. The use of MRI-guided focused ultrasounds to disrupt the blood-brain barrier could enhance the level of biomarkers in both blood and CSF. The detection of MYD88 L265P mutation with digital droplet PCR and the detection of ctDNA with next generation sequencing represent the best tools to diagnose and monitoring CNS lymphomas under treatment. In meningiomas, the low concentration of ctDNA is a limiting factor for the detection of driver mutations, such as NF2, AKTs, SMO, KLF4, TRAF7, SMARCB1, SMARCE1, PTEN, and TERT; an alternative approach could be the isolation of ctDNA through circulating extracellular vesicles. Liquid biopsies are being used extensively for diagnosis and surveillance of diffuse midline gliomas, in particular with the detection of the driver mutation H3K27M. Last, specific methylome patterns in CSF may allow the distinction of glioblastomas from CNS lymphomas or meningiomas.

SUMMARY

This review summarizes the current knowledge and future perspectives of liquid biopsy of blood and CSF for diagnosis and monitoring of primary CNS tumors.

Circulating Liquid Biopsy Biomarkers in Glioblastoma: Advances and Challenges

Gliomas, particularly glioblastoma (GBM), represent the most prevalent and aggressive tumors of the central nervous system (CNS). Despite recent treatment advancements, patient survival rates remain low. The diagnosis of GBM traditionally relies on neuroimaging methods such as magnetic resonance imaging (MRI) or computed tomography (CT) scans and postoperative confirmation via histopathological and molecular analysis. Imaging techniques struggle to differentiate between tumor progression and treatment-related changes, leading to potential misinterpretation and treatment delays. Similarly, tissue biopsies, while informative, are invasive and not suitable for monitoring ongoing treatments. These challenges have led to the emergence of liquid biopsy, particularly through blood samples, as a promising alternative for GBM diagnosis and monitoring. Presently, blood and cerebrospinal fluid (CSF) sampling offers a minimally invasive means of obtaining tumor-related information to guide therapy. The idea that blood or any biofluid tests can be used to screen many cancer types has huge potential. Tumors release various components into the bloodstream or other biofluids, including cell-free nucleic acids such as microRNAs (miRNAs), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), proteins, extracellular vesicles (EVs) or exosomes, metabolites, and other factors. These factors have been shown to cross the blood-brain barrier (BBB), presenting an opportunity for the minimally invasive monitoring of GBM as well as for the real-time assessment of distinct genetic, epigenetic, transcriptomic, proteomic, and metabolomic changes associated with brain tumors. Despite their potential, the clinical utility of liquid biopsy-based circulating biomarkers is somewhat constrained by limitations such as the absence of standardized methodologies for blood or CSF collection, analyte extraction, analysis methods, and small cohort sizes. Additionally, tissue biopsies offer more precise insights into tumor morphology and the microenvironment. Therefore, the objective of a liquid biopsy should be to complement and enhance the diagnostic accuracy and monitoring of GBM patients by providing additional information alongside traditional tissue biopsies. Moreover, utilizing a combination of diverse biomarker types may enhance clinical effectiveness compared to solely relying on one biomarker category, potentially improving diagnostic sensitivity and specificity and addressing some of the existing limitations associated with liquid biomarkers for GBM. This review presents an overview of the latest research on circulating biomarkers found in GBM blood or CSF samples, discusses their potential as diagnostic, predictive, and prognostic indicators, and discusses associated challenges and future perspectives.

Recent Advancements and Innovations in Pediatric Precision Oncology

Precision oncology incorporates comprehensive genomic profiling into the individualized clinical care of pediatric cancer patients. In recent years, comprehensive pan-cancer analyses have led to the successful implementation of genomics-based pediatric trials and accelerated approval of novel targeted agents. In addition, disease-specific studies have resulted in molecular subclassification of myriad cancer types with subsequent tailoring of treatment intensity based on the patient's prognostic factors. This review discusses the progress of the field and highlights developments that are leading to more personalized cancer care and improved patient outcomes. Increased understanding of the evolution of precision oncology over recent decades emphasizes the tremendous impact of improved genomic applications. New technologies and improved diagnostic modalities offer further promise for future advancements within the field.

Association of RAN and RANBP2 Gene Polymorphisms With Glioma Susceptibility in Chinese Children

BACKGROUND

Glioma is the most prevalent pediatric central nervous system malignancy. RAN, member RAS oncogene family (RAN), is a key signaling molecule that regulates the polymerization of microtubules during mitosis. RAN binding protein 2 (RANBP2) is involved in DNA replication, mitosis, metabolism, and tumorigenesis. The effects of RAN and RANBP2 gene polymorphisms on glioma susceptibility in Chinese children are currently unknown.

AIMS

This study aimed to evaluate the association between RAN and RANBP2 gene polymorphisms and glioma susceptibility in Chinese children.

METHODS AND RESULTS

We recruited 191 patients with glioma and 248 children without cancer for this case-control study. Polymerase chain reaction-based TaqMan was applied to gene sequencing and typing. Logistic regression model-calculated odds ratio and 95% confidence interval were used to verify whether the gene polymorphisms (RAN rs56109543 C>T, rs7132224 A>G, rs14035 C>T, and RANBP2 rs2462788 C>T) influence glioma susceptibility. Based on age, gender, tumor subtype, and clinical stage, stratified analyses of risk and protective genotypes were conducted. p values for mutant genotype analyses were all >0.05, indicating no significant correlation between these gene polymorphisms and glioma risk.

CONCLUSION

RAN and RANBP2 gene polymorphisms were not found to be statistically significantly associated with glioma susceptibility in Chinese children. Other potential functional gene polymorphism loci of RAN and RANBP2 will need to be evaluated in the search for novel glioma biomarkers.

Dietary factors and their influence on immunotherapy strategies in oncology: a comprehensive review

Immunotherapy is emerging as a promising avenue in oncology, gaining increasing importance and offering substantial advantages when compared to chemotherapy or radiotherapy. However, in the context of immunotherapy, there is the potential for the immune system to either support or hinder the administered treatment. This review encompasses recent and pivotal studies that assess the influence of dietary elements, including vitamins, fatty acids, nutrients, small dietary molecules, dietary patterns, and caloric restriction, on the ability to modulate immune responses. Furthermore, the article underscores how these dietary factors have the potential to modify and enhance the effectiveness of anticancer immunotherapy. It emphasizes the necessity for additional research to comprehend the underlying mechanisms for optimizing the efficacy of anticancer therapy and defining dietary strategies that may reduce cancer-related morbidity and mortality. Persistent investigation in this field holds significant promise for improving cancer treatment outcomes and maximizing the benefits of immunotherapy.

Purine salvage-associated metabolites as biomarkers for early diagnosis of esophageal squamous cell carcinoma: a diagnostic model-based study

Esophageal squamous cell carcinoma (ESCC) remains an important health concern in developing countries. Patients with advanced ESCC have a poor prognosis and survival rate, and achieving early diagnosis remains a challenge. Metabolic biomarkers are gradually gaining attention as early diagnostic biomarkers. Hence, this multicenter study comprehensively evaluated metabolism dysregulation in ESCC through an integrated research strategy to identify key metabolite biomarkers of ESCC. First, the metabolic profiles were examined in tissue and serum samples from the discovery cohort (n = 162; ESCC patients, n = 81; healthy volunteers, n = 81), and ESCC tissue-induced metabolite alterations were observed in the serum. Afterward, RNA sequencing of tissue samples (n = 46) was performed, followed by an integrated analysis of metabolomics and transcriptomics. The potential biomarkers for ESCC were further identified by censoring gene-metabolite regulatory networks. The diagnostic value of the identified biomarkers was validated in a validation cohort (n = 220), and the biological function was verified. A total of 457 dysregulated metabolites were identified in the serum, of which 36 were induced by tumor tissues. The integrated analyses revealed significant alterations in the purine salvage pathway, wherein the abundance of hypoxanthine/xanthine exhibited a positive correlation with HPRT1 expression and tumor size. A diagnostic model was developed using two purine salvage-associated metabolites. This model could accurately discriminate patients with ESCC from normal individuals, with an area under the curve (AUC) (95% confidence interval (CI): 0.680-0.843) of 0.765 in the external cohort. Hypoxanthine and HPRT1 exerted a synergistic effect in terms of promoting ESCC progression. These findings are anticipated to provide valuable support in developing novel diagnostic approaches for early ESCC and enhance our comprehension of the metabolic mechanisms underlying this disease.

Current Photodynamic Therapy for Glioma Treatment: An Update

Research on the development of photodynamic therapy for the treatment of brain tumors has shown promise in the treatment of this highly aggressive form of brain cancer. Analysis of both in vivo studies and clinical studies shows that photodynamic therapy can provide significant benefits, such as an improved median rate of survival. The use of photodynamic therapy is characterized by relatively few side effects, which is a significant advantage compared to conventional treatment methods such as often-used brain tumor surgery, advanced radiotherapy, and classic chemotherapy. Continued research in this area could bring significant advances, influencing future standards of treatment for this difficult and deadly disease.

Metabolomic profile of acute myeloid leukaemia parallels of prognosis and response to therapy

The heterogeneity of acute myeloid leukemia (AML), a complex hematological malignancy, is caused by mutations in myeloid cells affecting their differentiation and proliferation. Thus, various cytogenetic alterations in AML cells may be characterized by a unique metabolome and require different treatment approaches. In this study, we performed untargeted metabolomics to assess metabolomics differences between AML patients and healthy controls, AML patients with different treatment outcomes, AML patients in different risk groups based on the 2017 European LeukemiaNet (ELN) recommendations for the diagnosis and management of AML, AML patients with and without FLT3-ITD mutation, and a comparison between patients with FLT3-ITD, CBF-AML (Core binding factor acute myelogenous leukemia), and MLL AML (mixed-lineage leukemia gene) in comparison to control subjects. Analyses were performed in serum samples using liquid chromatography coupled with mass spectrometry (LC-MS). The obtained metabolomics profiles exhibited many alterations in glycerophospholipid and sphingolipid metabolism and allowed us to propose biomarkers based on each of the above assessments as an aid for diagnosis and eventual classification, allowing physicians to choose the best-suited treatment approach. These results highlight the application of LC-MS-based metabolomics of serum samples as an aid in diagnostics and a potential minimally invasive prognostic tool for identifying various cytogenetic and treatment outcomes of AML.

Alterations in cellular metabolism under different grades of glioma staging identified based on a multi-omics analysis strategy

Glioma is a type of brain tumor closely related to abnormal cell metabolism. Firstly, multiple combinatorial sequencing studies have revealed this relationship. Genomic studies have identified gene mutations and gene expression disorders related to the development of gliomas, which affect cell metabolic pathways. In addition, transcriptome studies have revealed the genes and regulatory networks that regulate cell metabolism in glioma tissues. Metabonomics studies have shown that the metabolic pathway of glioma cells has changed, indicating their distinct energy and nutritional requirements. This paper focuses on the retrospective analysis of multiple groups combined with sequencing to analyze the changes in various metabolites during metabolism in patients with glioma. Finally, the changes in genes, regulatory networks, and metabolic pathways regulating cell metabolism in patients with glioma under different metabolic conditions were discussed. It is also proposed that multi-group metabolic analysis is expected to better understand the mechanism of abnormal metabolism of gliomas and provide more personalized methods and guidance for early diagnosis, treatment, and prognosis evaluation of gliomas.

Liquid biopsy: creating opportunities in brain space

In recent years, liquid biopsy has emerged as an alternative method to diagnose and monitor tumors. Compared to classical tissue biopsy procedures, liquid biopsy facilitates the repetitive collection of diverse cellular and acellular analytes from various biofluids in a non/minimally invasive manner. This strategy is of greater significance for high-grade brain malignancies such as glioblastoma as the quantity and accessibility of tumors are limited, and there are collateral risks of compromised life quality coupled with surgical interventions. Currently, blood and cerebrospinal fluid (CSF) are the most common biofluids used to collect circulating cells and biomolecules of tumor origin. These liquid biopsy analytes have created opportunities for real-time investigations of distinct genetic, epigenetic, transcriptomics, proteomics, and metabolomics alterations associated with brain tumors. This review describes different classes of liquid biopsy biomarkers present in the biofluids of brain tumor patients. Moreover, an overview of the liquid biopsy applications, challenges, recent technological advances, and clinical trials in the brain have also been provided.

Glioma and post-translational modifications: A complex relationship

Post-translational modifications (PTMs) are common covalent processes in biochemical pathways that alter protein function and activity. These modifications occur through proteolytic cleavage or attachment of modifying groups, such as phosphoryl, methyl, glycosyl, or acetyl groups, with one or more amino acid residues of a single protein. Some PTMs also present crosstalk abilities that affect both protein functionality and structure, creating new proteoforms. Any alteration in organism homeostasis may be a cancer hallmark. Cataloging PTMs and consequently, emerging proteoforms, present new therapeutic targets, approaches, and opportunities to discover additional discriminatory biomarkers in disease diagnostics. In this review, we focus on experimentally confirmed PTMs and their potential crosstalk in glioma research to introduce new opportunities for this tumor type, which emerge within the PTMomics area.

Comprehensive clinical assays for molecular diagnostics of gliomas: the current state and future prospects

Glioma is one of the most intractable types of cancer, due to delayed diagnosis at advanced stages. The clinical symptoms of glioma are unclear and due to a variety of glioma subtypes, available low-invasive testing is not effective enough to be introduced into routine medical laboratory practice. Therefore, recent advances in the clinical diagnosis of glioma have focused on liquid biopsy approaches that utilize a wide range of techniques such as next-generation sequencing (NGS), droplet-digital polymerase chain reaction (ddPCR), and quantitative PCR (qPCR). Among all techniques, NGS is the most advantageous diagnostic method. Despite the rapid cheapening of NGS experiments, the cost of such diagnostics remains high. Moreover, high-throughput diagnostics are not appropriate for molecular profiling of gliomas since patients with gliomas exhibit only a few diagnostic markers. In this review, we highlighted all available assays for glioma diagnosing for main pathogenic glioma DNA sequence alterations. In the present study, we reviewed the possibility of integrating routine molecular methods into the diagnosis of gliomas. We state that the development of an affordable assay covering all glioma genetic aberrations could enable early detection and improve patient outcomes. Moreover, the development of such molecular diagnostic kits could potentially be a good alternative to expensive NGS-based approaches.

A comparison of different machine-learning techniques for the selection of a panel of metabolites allowing early detection of brain tumors

Metabolomics combined with machine learning methods (MLMs), is a powerful tool for searching novel diagnostic panels. This study was intended to use targeted plasma metabolomics and advanced MLMs to develop strategies for diagnosing brain tumors. Measurement of 188 metabolites was performed on plasma samples collected from 95 patients with gliomas (grade I-IV), 70 with meningioma, and 71 healthy individuals as a control group. Four predictive models to diagnose glioma were prepared using 10 MLMs and a conventional approach. Based on the cross-validation results of the created models, the F1-scores were calculated, then obtained values were compared. Subsequently, the best algorithm was applied to perform five comparisons involving gliomas, meningiomas, and controls. The best results were obtained using the newly developed hybrid evolutionary heterogeneous decision tree (EvoHDTree) algorithm, which was validated using Leave-One-Out Cross-Validation, resulting in an F1-score for all comparisons in the range of 0.476-0.948 and the area under the ROC curves ranging from 0.660 to 0.873. Brain tumor diagnostic panels were constructed with unique metabolites, which reduces the likelihood of misdiagnosis. This study proposes a novel interdisciplinary method for brain tumor diagnosis based on metabolomics and EvoHDTree, exhibiting significant predictive coefficients.

HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas

BACKGROUND

Gliomas are the most frequent type of central nervous system tumor, accounting for more than 70% of all malignant CNS tumors. Recent research suggests that the hyaluronan-mediated motility receptor (HMMR) could be a novel potential tumor prognostic marker. Furthermore, mounting data has highlighted the important role of ceRNA regulatory networks in a variety of human malignancies. The complexity and behavioural characteristics of HMMR and the ceRNA network in gliomas, on the other hand, remained unknown.

METHODS

Transcriptomic expression data were collected from TCGA, GTEx, GEO, and CGGA database.The relationship between clinical variables and HMMR was analyzed with the univariate and multivariate Cox regression. Kaplan-Meier method was used to assess OS. TCGA data are analyzed and processed, and the correlation results obtained were used to perform GO, GSEA, and ssGSEA. Potentially interacting miRNAs and lncRNAs were predicted by miRWalk and StarBase.

RESULTS

HMMR was substantially expressed in gliomas tissues compared to normal tissues. Multivariate analysis revealed that high HMMR expression was an independent predictive predictor of OS in TCGA and CGGA. Functional enrichment analysis found that HMMR expression was associated with nuclear division and cell cycle. Base on ssGSEA analysis, The levels of HMMR expression in various types of immune cells differed significantly. Bioinformatics investigation revealed the HEELPAR-hsa-let-7i-5p-RRM2 ceRNA network, which was linked to gliomas prognosis. And through multiple analysis, the good predictive performance of HELLPAR/RRM2 axis for gliomas patients was confirmed.

CONCLUSION

This study provides multi-layered and multifaceted evidence for the importance of HMMR and establishes a HMMR-related ceRNA (HEELPAR-hsa-let-7i-5p-RRM2) overexpressed network related to the prognosis of gliomas.

Metabolomic and Lipidomic Profiling of Gliomas-A New Direction in Personalized Therapies

Simple Summary

Gliomas comprise an extremely diverse category of brain tumors that are difficult to diagnose and treat. As a result, scientists continue to search for new treatment solutions, with personalized medicine having emerged as a particularly promising therapeutic approach. Metabolomics and its sub-discipline, lipidomics, are two scientific fields well-suited to support this search. Metabolomics focuses on the physicochemical changes in the metabolome, which include all of the small endogenous and exogenous compounds in a biological system. As such, metabolic analysis can help identify important biochemical pathways which could be the targets for new therapeutic approaches. This review examines the new directions of personalized therapies for gliomas and how metabolomic and lipidomic analysis assists in developing these strategies and monitoring their effectiveness. The discussion of new strategies is preceded by a brief overview of the current “gold standard” treatment for gliomas and the obstacles that new treatment approaches must overcome.

Abstract

In addition to being the most common primary brain tumor, gliomas are also among the most difficult to diagnose and treat. At present, the “gold standard” in glioma treatment entails the surgical resection of the largest possible portion of the tumor, followed by temozolomide therapy and radiation. However, this approach does not always yield the desired results. Additionally, the ability to cross the blood-brain barrier remains a major challenge for new potential drugs. Thus, researchers continue to search for targeted therapies that can be individualized based on the specific characteristics of each case. Metabolic and lipidomic research may represent two of the best ways to achieve this goal, as they enable detailed insights into the changes in the profile of small molecules in a biological system/specimen. This article reviews the new approaches to glioma therapy based on the analysis of alterations to biochemical pathways, and it provides an overview of the clinical results that may support personalized therapies in the future.