AIMC Topic: Biomarkers, Tumor

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Machine learning driven prediction of drug efficacy in lung cancer: based on protein biomarkers and clinical features.

Life sciences
Currently, chemotherapy drugs are the first-line treatment for lung cancer patients, and evaluating their efficacy is of utmost significance. However, assessing the clinical efficacy of chemotherapy drugs remains a challenging task. In recent years, ...

Unraveling the Role of Gut Microbiota in Colorectal Cancer: A Global Perspectives and Biomarkers as Early Screening Tool for Colorectal Cancer.

Studies in health technology and informatics
Colorectal cancer (CRC), the second deadliest cancer globally, is closely tied to gut microbiota, opening doors for early detection and treatment. This review of 45 studies (2018-2024) highlights microbial biomarkers like Fusobacterium nucleatum, Bac...

Detection of Brain Cancer Using Genome-wide Cell-free DNA Fragmentomes.

Cancer discovery
UNLABELLED: Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer diagnosis. In this study, we analyzed genome-wide c...

Developing risk stratification strategies and biomarkers for recurrent hepatocellular carcinoma.

Clinical and translational medicine
Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, with high rates of post-resection recurrence posing significant clinical challenges. Early recurrence is largely driven by aggressive tumor biology, while late recurr...

A robust machine learning model based on ribosomal-subunit-derived piRNAs for diagnostic potential of nonsmall cell lung cancer across multicentre, large-scale of sequencing data.

Clinical and translational medicine
Nonsmall cell lung cancer (NSCLC) is a lethal cancer and lacks robust biomarkers for noninvasive clinical diagnosis. Detecting NSCLC at the early stage can decrease the mortality rate and minimise harm caused by various treatments. We curated 2050 sa...

A multi-phase approach using supervised algorithms and clinical models to generate high-accuracy signatures for pancreatic cancer.

Computers in biology and medicine
BACKGROUND: The in silico analyses provide evidence supporting the potential of methylation-driven differentially expressed genes as therapeutic targets across cancer types. This leads us to identify novel targets and their associated drug compounds ...

Integration of machine learning in biomarker discovery for esophageal squamous cell carcinoma: Applications and future directions.

Pathology, research and practice
PURPOSE: Recent advancements in sequencing technologies and bioinformatics algorithms have facilitated significant breakthroughs in both fundamental and clinical tumor research. Nevertheless, the processing and utilization of large-scale data continu...

The Construction of a New Prognostic Model of Breast Cancer and the Exploration of Drug Sensitivity Based on Machine Learning for Glycosylation-Related Genes.

Clinical breast cancer
AIMS: Breast cancer has become the number 1 killer threatening women's health. In recent years, glycosylation modification has played an increasingly important role in tumor progression. The aim of this study was to explore the key genes that may be ...

Infrared and Raman spectroscopy of blood plasma for rapid endometrial cancer detection.

British journal of cancer
BACKGROUND: Endometrial cancer (EC) is the 6th most common cancer among women worldwide. No effective non-invasive screening methods or approved blood biomarkers for EC exist. Previous research explored Attenuated Total Reflection-Fourier Transform I...

Detection of Early-Stage Colorectal Cancer Using Cell-Free oncRNA Biomarkers and Artificial Intelligence.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Colorectal cancer is the second leading cause of cancer-related deaths worldwide, and early detection significantly improves treatment outcomes, but existing blood-based tests often have limited sensitivity in early-stage disease. We develop...