Other Cancers

Endothelial Metabolic Zonation in the Vascular Network: A Spatiotemporal Blueprint for Angiogenesis.

Angiogenesis, a cornerstone of vascular development, tissue regeneration, and tumor progression, is critically orchestrated by the metabolic behavior of endothelial cells (ECs). Recent discoveries have redefined ECs not as metabolically uniform entities, but as spatially and functionally heterogeneous populations whose metabolic states govern their angiogenic potential. This review presents a comp...

Aptamer-directed siRNA delivery systems for triple-negative breast cancer therapy.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by the absence of estrogen, progesterone, and HER2 receptors, making it unresponsive to targeted hormonal and HER2-based therapies. Current treatment options, including chemotherapy and radiation, have limited efficacy and are associated with severe side effects, emphasizing the need for innovative therape...

Unraveling the role of perineural invasion in cancer progression across multiple tumor types.

Perineural invasion (PNI) refers to the infiltration of tumor cells into the connective tissue of nerves and is increasingly recognized as a pathologi...

Multivariate Screening and Automated Clustering of Macrophage Immunoreactome to Nanoparticles and Photothermal Therapy.

Immunotherapy aims to control the immune system against diseases such as cancer or infections. Nanotechnology is part of the armamentarium to reprogra...

A machine learning model integrating clinical-radiomics-deep learning features accurately predicts postoperative recurrence and metastasis of primary gastrointestinal stromal tumors.

OBJECTIVES: Post-surgical prediction of recurrence or metastasis for primary gastrointestinal stromal tumors (GISTs) remains challenging. We aim to de...

Multi-site validation of an interpretable model to analyze breast masses.

An external validation of IAIA-BL-a deep-learning based, inherently interpretable breast lesion malignancy prediction model-was performed on two patie...

The impact of intensity discretisation and filtration on the performance of the radiomic and machine learning models in brain metastasis patients treated with gamma knife radiosurgery.

INTRODUCTION: Image preprocessing is crucial for optimizing radiomics feature extraction, however, inconsistencies in the implementation process and a...

Two-stage ensemble learning framework for automated classification of keratoconus severity.

BACKGROUND AND OBJECTIVE: Accurate staging of keratoconus (KC) is crucial for timely intervention and improving patient quality of life. Unlike prior ...

Diagnostic Performance of Radiomics for Differentiating Intrahepatic Cholangiocarcinoma from Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

BACKGROUND: Differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) is essential for selecting the most effective tr...

Intra-tumor microbiome-based tumor survival indices predict immune interaction and drug sensitivity on pan-cancer scale.

UNLABELLED: Growing research evidence indicates a substantial influence of the intra-tumor microbiome on tumor outcome. However, there is currently no...

Exploring the complex interplay between oral infection, periodontitis, and robust microRNA induction, including multiple known oncogenic miRNAs.

() is an oral commensal bacterium that can become pathogenic and is associated with periodontitis, adverse pregnancy outcomes, and colorectal cancer ...

Risk Classification of Low-Resolution Whole-Slide Thumbnail Images by Multi-dimensional Feature Reconstruction with Multi-task Deep Learning Network Helps Prioritize Pathology Case Registration.

Contemporary surgical pathology workflows often prioritize slide examination based on case registry order rather than patient risk level. As a result,...

Integrated transcriptome analysis and combinatorial machine learning to construct a homeostatic model of acetylation for ccRCC and validate the key gene GCNT4.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors of the urinary system. Protein acetylation plays a key ...

Machine learning-driven national analysis for predicting adverse outcomes in intramedullary spinal cord tumor surgery.

UNLABELLED: Spinal tumors represent 15% of all central nervous system malignancies, with intramedullary spinal cord tumors (IMSCTs) being rare. Predom...

Deep learning algorithms from histopathological images stratify molecular subtypes for leiomyosarcoma: a proof-and-concept diagnostic study.

BACKGROUND: The leiomyosarocma (LMS) is the most common soft tissue sarcoma, and its molecular subtypes were identified with therapeutic sensitivity a...

Differentiating adenocarcinoma and squamous cell carcinoma in lung cancer using semi automated segmentation and radiomics.

INTRODUCTION: Adenocarcinoma (AD) and squamous cell carcinoma (SCC) are frequently observed forms of non-small cell lung cancer (NSCLC), playing a sig...

Advances and Integrations of Computer-Assisted Planning, Artificial Intelligence, and Predictive Modeling Tools for Laser Interstitial Thermal Therapy in Neurosurgical Oncology.

Laser interstitial thermal therapy (LiTT) has emerged as a minimally invasive, MRI-guided treatment of brain tumors that are otherwise considered inop...

Non-invasive prediction of NSCLC immunotherapy efficacy and tumor microenvironment through unsupervised machine learning-driven CT Radiomic subtypes: a multi-cohort study.

BACKGROUND: Radiomics analyzes quantitative features from medical images to reveal tumor heterogeneity, offering new insights for diagnosis, prognosis...

Preoperative Assessment of Lymph Node Metastasis in Rectal Cancer Using Deep Learning: Investigating the Utility of Various MRI Sequences.

PURPOSE: This study aimed to develop a deep learning (DL) model based on three-dimensional multi-parametric magnetic resonance imaging (mpMRI) for pre...

Diagnostic Study of Head and Neck Metastatic Tumors From Different Primary Sites Based on Stacking Machine Learning Methods.

Metastatic tumors of the head and neck (MTHN) typically indicate advanced disease with a poor prognosis, originating from cells that spread from other...