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Bladder cancer is a significant health concern worldwide, necessitating effective diagnostic and monitoring strategies. Biomarkers play a crucial role in the early detection, prognosis, and treatment of this disease. This review explores the current landscape of bladder cancer biomarkers, including FDA-approved molecular biomarkers and emerging ones. FDA-approved molecular biomarkers, such as BTA stat, BTA TRAK, and NMP22, have been instrumental in diagnosing and monitoring bladder cancer. These biomarkers are derived from urinary samples and are particularly useful due to their sensitivity and specificity. As we move forward, we should continue to seek ways to optimize our processes and outcomes, these markers remain seriously challenged in the detection of early bladder cancer due to their limited sensitivity and specificity. For instance, sensitivities of BTA stat in bladder tumor detection have varied between 40-72%, while its specificities vary from 29-96%. In the same way, 70% sensitivity and 80% specificity have been recorded for BTA TRAK, while 11-85.7% sensitivity and 77-100% specificity have been documented for NMP22 BladderChek. The given variations, especially the low sensitivity in the diagnosis of bladder cancer at an early stage call for the invention of better diagnostic systems. Moreover, different sample collection and handling procedures applied in different laboratories further contribute to inconsistent results obtained. Extracellular vesicles (EVs) and exosomes, which carry a vast number of proteins, are being considered as potential biomarkers. Although these markers show promise, challenges remain due to non-standardized isolation techniques and lack of reproducibility across studies. Moreover, the discovery of new potential biomarkers is ongoing. For instance, the UBC® Rapid test and UBC ELISA kit, the XPERT BC Monitor, BC UroMark, TaqMan® Arrays, Soluble FAS (sFAS), Bladder tumor fibronectin (BTF), and IGF2 and MAGE-A3 are among the newest biomarkers under investigation. In conclusion, while bladder cancer biomarkers have shown great promise, more research is needed to standardize the testing procedures and validate these biomarkers in a clinical setting. This will pave the way for more accurate and efficient diagnosis and monitoring of bladder cancer, ultimately improving patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Accurate differentiation between lung adenocarcinoma (AC) and lung squamous cell carcinoma (SCC) is crucial owing to their distinct therapeutic approaches. MicroRNAs (miRNAs) exhibit variable expression across subtypes, making them promising biomarkers for discrimination. This study aimed to identify miRNAs with robust discriminatory potential between AC and SCC and elucidate their clinical significance. Methods: MiRNA expression profiles for AC and SCC patients were obtained from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and supervised machine learning methods (Support Vector Machine, Decision trees and Naïve Bayes) were employed. Clinical significance was assessed through receiver operating characteristic (ROC) curve analysis, survival analysis, and correlation with clinicopathological features. Validation was conducted using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Furthermore, signaling pathway and gene ontology enrichment analyses were conducted to unveil biological functions. Results: Five miRNAs (miR-205-3p, miR-205-5p, miR-944, miR-375 and miR326) emerged as potential discriminative markers. The combination of miR-944 and miR-326 yielded an impressive area under the curve of 0.985. RT-qPCR validation confirmed their biomarker potential. miR-326 and miR-375 were identified as prognostic factors in AC, while miR-326 and miR-944 correlated significantly with survival outcomes in SCC. Additionally, exploration of signaling pathways implicated their involvement in key pathways including PI3K-Akt, MAPK, FoxO, and Ras. Conclusion: This study enhances our understanding of miRNAs as discriminative markers between AC and SCC, shedding light on their role as prognostic indicators and their association with clinicopathological characteristics. Moreover, it highlights their potential involvement in signaling pathways crucial in non-small cell lung cancer pathogenesis. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is an aggressive and diffuse type of glioma with the lowest survival rate in patients. The recent failure of multiple treatments suggests that targeting several targets at once may be a different strategy to overcome GBM carcinogenesis. Normal function of oncogenes and tumor suppressor genes need for the preservation of regular cellular processes, so any defects in these genes' activity, operate the corresponding signaling pathways, which initiate carcinogenic processes. Long non-coding RNAs (lncRNAs) that can be found in the cytoplasm or nucleus of the cells, control the transcription and translation of genes. LncRNAs perform a variety of functions, including epigenetic alteration, protein modification and stability, transcriptional regulation, and competition for miRNA that regulate mRNA translation through sponging miRNAs. Identification of various oncogenic lncRNAs and their multiple roles in brain cancers making them potential candidates for use as glioma diagnostic, prognostic, and therapeutic targets in the future. This study highlighted multiple oncogenic lncRNAs and classified them into different signaling pathways based on the regulated target genes in glioblastoma. [ABSTRACT FROM AUTHOR]