miRNA Biomarkers in Prostate Cancer: Leveraging Machine Learning for Improved Diagnostic Accuracy DOI Creative Commons
Shweta Singh, Abhay Kumar Pathak, Sukhad Kural

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 28, 2024

ABSTRACT Prostate cancer (PCa) diagnosis often relies on prostate-specific antigen (PSA) testing, but its high false-positive rates lead to unnecessary biopsies. MicroRNAs (miRNAs) have emerged as promising non-invasive biomarkers for detection due their stability in biological fluid and disease specificity. Despite potential, the clinical translation of miRNAs is hindered by several challenges - population-based variability, environmental Factors, methodological Inconsistencies, lack standardization, normalization Issues, complexity System. These factors significantly impact consistency miRNA expression readouts, particularly terms Ct-values, across different studies, which turn affects determination cutoff values that are crucial a diagnostic setup. This preliminary study offers pilot demonstration integrating biomarker with machine learning (ML), can help identify patterns improve classification, potentially reducing reliance fixed certain contexts pave path wider translation. We analyzed key (miR-21-5p, miR-221-3p, miR-141-3p) blood samples from patients PCa benign prostatic hyperplasia (BPH). Utilizing Random Forest classifier, we achieved an accuracy 77.42%, precision 86.21%, recall 71.43%, AUC-ROC score 0.78. The application ML enabled us leverage complex features, such combinations ratios data, enhanced robustness reliability model. Additionally, bioinformatics analysis preferential features identified model confirmed relevance these PCa-related pathways, further supporting potential biomarkers. In future, poised enhance performance compared traditional linear analyses limited set While our did not explore multiple populations or effects variables, it highlights demonstrating improved eliminating need values. capability could broaden applicability miRNA-based diagnostics, making them more reliable actionable settings. However, fully realize this validation larger diverse cohorts essential. Overall, lays groundwork utilizing ML-enhanced panels powerful tools early future practice. Graphical Abstract

Язык: Английский

The current status of miRNA in urinary bladder cancer: A minireview and strength, weakness, opportunity, and threat analysis DOI Creative Commons

R. M. Tripathy,

Lalit Kumar,

Sukhad Kural

и другие.

Indian Journal of Urology, Год журнала: 2025, Номер 41(2), С. 98 - 103

Опубликована: Апрель 1, 2025

ABSTRACT MicroRNAs, small noncoding RNA molecules, are critical in modulating gene expression and contribute substantially to the initiation progression of urinary bladder cancer (UBCa), a major malignancy affecting people globally. UBCa is known for its high recurrence rates significant heterogeneity. The stability miRNAs body fluids such as urine blood excellent potential noninvasive markers early detection, monitoring treatment progress, predicting outcomes patients with UBCa. In addition, could also improve effectiveness immunotherapy support development personalized strategies. Despite their potential, challenges variability shortcomings delivery systems must be carefully addressed. This strength, weakness, opportunity, threat (SWOT) analysis highlights crucial role explores advancing precision oncology.

Язык: Английский

Процитировано

1
Prospective Assessment of VI-RADS with Muscle Invasion in Urinary Bladder Cancer and Its Implication on Re-Resection/Restaging TURBT Patients DOI
Sukhad Kural, Abhay Kumar Pathak, Shweta Singh

и другие.

Annals of Surgical Oncology, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 4, 2024

Язык: Английский

Процитировано

6
Understanding the Role of MicroRNAs in Congenital Tooth Agenesis: A Multi-omics Integration DOI
Prashant Ranjan, Chandra Devi, Neha Verma

и другие.

Biochemical Genetics, Год журнала: 2025, Номер unknown

Опубликована: Фев. 22, 2025

Язык: Английский

Процитировано

0
CNN-based Classification of Bladder Tissue Lesions from Endoscopy Images DOI Creative Commons

Lutviana Lutviana,

Rian Ardianto,

Purwono Purwono

и другие.

IT JOURNAL RESEARCH AND DEVELOPMENT, Год журнала: 2025, Номер 9(2), С. 95 - 107

Опубликована: Март 10, 2025

Bladder cancer is one type of tumor that frequently occurs in the urinary system, and early diagnosis essential to improve prognosis survival patients. The study aims develop a Convolutional Neural Network (CNN) model for bladder tissue lesion classification from endoscopic images. This uses dataset consisting 1754 images, which are divided into four classes: High-Grade Cancer (HGC), Low-Grade (LGC), Non-Specific Tissue (NST), Non-Tumorous Lesion (NTL). proposed CNN showed validation accuracy 96.29%, with high recall, precision, F1-score most classes. results show CNN-based automated methods can efficiency cancer, reduce manual visual interpretation errors, quality patient care. suggests increasing training data, especially NTL class, applying more complex architecture better results.

Язык: Английский

Процитировано

0
Assessing the clinical efficacy of neoadjuvant intravesical Mitomycin C in naïve non-muscle invasive urinary bladder cancer: A systematic review and meta-analysis DOI

Anuja Thakur,

Lalit Kumar, Sakshi Agarwal

и другие.

Current Problems in Cancer, Год журнала: 2025, Номер unknown, С. 101198 - 101198

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Unraveling the multifaceted roles of extracellular vesicles in bladder cancer: diagnostic insights and therapeutic opportunities DOI Creative Commons

Kaibin Huang,

Chen Yang,

Yanfang Xu

и другие.

Frontiers in Oncology, Год журнала: 2025, Номер 15

Опубликована: Май 6, 2025

Bladder cancer, predominantly urothelial carcinoma, is a global health issue with increasing incidences and mortality. It poses significant diagnostic therapeutic challenges due to its molecular heterogeneity the limitations of current detection methods. Extracellular vesicles (EVs), including exosomes, play crucial role in intercellular communication have emerged as potential biomarkers agents bladder cancer. This review focuses on multifaceted roles EVs cancer biology, their biomarkers, use strategies. We discuss how reflect subtypes participate metabolic reprogramming angiogenesis, modulate cellular behavior. The also highlights advances proteomic analysis urinary tissue-exudative EVs, identifying specific proteins RNAs that could serve non-invasive markers. Furthermore, we explore innovative natural nanocarriers for drug delivery treatment, demonstrating enhance efficacy chemotherapy selectively target cells. integration EV-based diagnostics traditional methods lead more personalized effective management, emphasizing need further research clinical validation.

Язык: Английский

Процитировано

0
Immunomodulatory effects of immune cell-derived extracellular vesicles in melanoma DOI Creative Commons

Peng Nanru

Frontiers in Immunology, Год журнала: 2024, Номер 15

Опубликована: Сен. 26, 2024

Melanoma, recognized as one of the most immunogenic malignancies in humans, holds paramount significance realm immunotherapy. However, emergence drug resistance and occurrence adverse reactions underscore pressing need to explore increasingly personalized immunotherapeutic modalities. Extracellular Vesicles (EVs), pivotal derivatives immune cells, assume roles by encapsulating proteins, lipids, nucleic acids within bilayer lipid structures, thereby facilitating targeted delivery other cells. This orchestrated process orchestrates critical functions including antigen presentation, modulation, induction apoptosis tumor A burgeoning body evidence underscores vast therapeutic potential EVs melanoma treatment. comprehensive review aims delineate derived from cells such dendritic natural killer macrophages, T context patients, furnishing invaluable insights for future direction

Язык: Английский

Процитировано

1
Understanding Tooth Agenesis: A Multi-omics Insight into MicroRNA Regulation DOI Creative Commons
Prashant Ranjan, Chandra Devi, Neha Verma

и другие.

Опубликована: Сен. 3, 2024

Abstract This study reveals novel microRNAs (miRNAs) implicated in congenital tooth agenesis (CTA), a common dental anomaly with complex genetic basis. Through multi-omics approach combining bioinformatics, whole exome sequencing, metabolite analysis, and gene expression profiling, we identified eight key miRNAs potentially involved development. Among these, four viz. miR-218-5p, miR-15b-5p, miR-200b-3p, let-7a-3p were validated as significant regulators CTA, marking their first investigation blood samples from CTA patients. Our analysis revealed that these play critical roles odontogenesis, influencing essential signaling pathways, including Wnt, FGF , PI3 kinase pathways. four, miR-218-5p emerged players tissue morphogenesis, each contributing to previously unidentified networks crucial for highlights the potential of non-invasive biomarkers early diagnosis therapeutic targets. is comprehensive specific utilizing offer fresh insights into miRNA-mediated mechanisms role regulating anomalies. findings not only advance understanding regulation development but also pave way personalized approaches managing Further research needed validate results explore clinical applications. Graphical

Язык: Английский

Процитировано

0
miRNA Biomarkers in Prostate Cancer: Leveraging Machine Learning for Improved Diagnostic Accuracy DOI Creative Commons
Shweta Singh, Abhay Kumar Pathak, Sukhad Kural

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 28, 2024

ABSTRACT Prostate cancer (PCa) diagnosis often relies on prostate-specific antigen (PSA) testing, but its high false-positive rates lead to unnecessary biopsies. MicroRNAs (miRNAs) have emerged as promising non-invasive biomarkers for detection due their stability in biological fluid and disease specificity. Despite potential, the clinical translation of miRNAs is hindered by several challenges - population-based variability, environmental Factors, methodological Inconsistencies, lack standardization, normalization Issues, complexity System. These factors significantly impact consistency miRNA expression readouts, particularly terms Ct-values, across different studies, which turn affects determination cutoff values that are crucial a diagnostic setup. This preliminary study offers pilot demonstration integrating biomarker with machine learning (ML), can help identify patterns improve classification, potentially reducing reliance fixed certain contexts pave path wider translation. We analyzed key (miR-21-5p, miR-221-3p, miR-141-3p) blood samples from patients PCa benign prostatic hyperplasia (BPH). Utilizing Random Forest classifier, we achieved an accuracy 77.42%, precision 86.21%, recall 71.43%, AUC-ROC score 0.78. The application ML enabled us leverage complex features, such combinations ratios data, enhanced robustness reliability model. Additionally, bioinformatics analysis preferential features identified model confirmed relevance these PCa-related pathways, further supporting potential biomarkers. In future, poised enhance performance compared traditional linear analyses limited set While our did not explore multiple populations or effects variables, it highlights demonstrating improved eliminating need values. capability could broaden applicability miRNA-based diagnostics, making them more reliable actionable settings. However, fully realize this validation larger diverse cohorts essential. Overall, lays groundwork utilizing ML-enhanced panels powerful tools early future practice. Graphical Abstract

Язык: Английский

Процитировано

0