Cytokine Profile in Development of Glioblastoma in Relation to Healthy Individuals

Diagnostic and Prognostic Value of Circulating DNA Fragments in Glioblastoma Multiforme Patients

Novel blood-circulating molecules, as potential biomarkers for glioblastoma multiforme (GBM) diagnosis and monitoring, are attracting particular attention due to limitations of imaging modalities and invasive tissue biopsy procedures. This study aims to assess the diagnostic and prognostic values of circulating cell-free DNA (cfDNA) in relation to inflammatory status in GBM patients and to determine the concentration and average size of DNA fragments typical of tumour-derived DNA fractions. Preoperative plasma samples from 40 patients (GBM 65.0 ± 11.3 years) and 40 healthy controls (HC 70.4 ± 5.4 years) were compared. The cfDNA concentrations and lengths were measured using the electrophoresis platform, and inflammatory indices (NLR, PLR, LMR, and SII) were calculated from complete blood cell analysis. More fragmented cfDNA and 4-fold higher 50-700 bp cfDNA concentrations were detected in GBM patients than in healthy controls. The average cfDNA size in the GBM group was significantly longer (median 336 bp) than in the HC group (median 271 bp). Optimal threshold values were 1265 pg/μL for 50-700 bp cfDNA (AUC = 0.857) and 290 bp for average cfDNA size (AUC = 0.814). A Kaplan-Meier survival curves analysis also demonstrated a higher mortality risk in the GBM group with a cut-off >303 bp cfDNA. This study is the first to have revealed glioblastoma association with high levels of cfDNA > 1000 pg/μL of 50-700 bp in length, which can be aggravated by immunoinflammatory reactivity.

An Overview of Advances in Rare Cancer Diagnosis and Treatment

Cancer stands as the leading global cause of mortality, with rare cancer comprising 230 distinct subtypes characterized by infrequent incidence. Despite the inherent challenges in addressing the diagnosis and treatment of rare cancers due to their low occurrence rates, several biomedical breakthroughs have led to significant advancement in both areas. This review provides a comprehensive overview of state-of-the-art diagnostic techniques that encompass new-generation sequencing and multi-omics, coupled with the integration of artificial intelligence and machine learning, that have revolutionized rare cancer diagnosis. In addition, this review highlights the latest innovations in rare cancer therapeutic options, comprising immunotherapy, targeted therapy, transplantation, and drug combination therapy, that have undergone clinical trials and significantly contribute to the tumor remission and overall survival of rare cancer patients. In this review, we summarize recent breakthroughs and insights in the understanding of rare cancer pathophysiology, diagnosis, and therapeutic modalities, as well as the challenges faced in the development of rare cancer diagnosis data interpretation and drug development.