Other Cancers

Decoding Senescence-Driven Heterogeneity in Early-Onset Colorectal Cancer for Prognostic and Therapeutic Stratification.

Early-onset colorectal cancer (EOCRC), diagnosed in patients under 50, is particularly aggressive, yet lacks targeted therapeutic strategies. This study aimed to explore the role of cellular senescence in driving EOCRC's malignancy and developed a senescence scoring system (EO-Senscore) to guide precision oncology. Through a multi-omics analysis of 2961 patients, we discovered that cellular senesc...

Innovative molecular diagnostic strategy for salivary gland lesions based on ATR-FTIR spectroscopy coupled with machine learning.

OBJECTIVE: This study aimed to identify the biochemical signatures that distinguish pleomorphic adenoma (PA) and mucoepidermoid carcinoma (MEC) from normal parotid tissue (NP), while also exploring molecular differences relevant to benign-malignant tumor differentiation using Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with machine-learning (ML) approac...

Polyploid giant cancer cells: A novel target in future cancer therapy.

Under intense therapeutic stress-including chemotherapy, radiotherapy, and targeted therapies-tumor cells can undergo ploidy reprogramming to generate...

Chemotherapy-Sparing Strategies in Follicular Lymphoma: Emerging Targeted and Immune-Based Approaches.

Follicular lymphoma (FL), traditionally considered an indolent yet incurable malignancy, is experiencing a substantial evolution in its therapeutic la...

Causal Inference and Prognostic Modeling in Colorectal Cancer through Integration of Computational Pathology and Mendelian Randomization.

BACKGROUND: While traditional pathology supports the diagnosis and staging of colorectal cancer (CRC), computational pathology provides novel prognost...

Ensemble learning-based radiomics model for predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

PURPOSE: To develop and validate a multimodal ensemble machine learning model integrating multi-sequence magnetic resonance imaging (MRI) radiomics, c...

Augmented intelligence for multimodal virtual biopsy in breast cancer using generative artificial intelligence.

OBJECTIVE: This study aims to propose a multimodal, multi-view deep learning approach for breast cancer virtual biopsy, a non-invasive classification ...

HepatoAILFA: Machine-Learning-Assisted Nano-enhanced Point-of-Care System for Personalized Precise Diagnosis of Hepatocellular Carcinoma.

Early diagnosis significantly improves survival rates for hepatocellular carcinoma (HCC), yet traditional methods face limitations, including speciali...

Post-Translational Modification Mediated By Acylation Modification Related Genes Induces Immunosuppression and Immunotherapy Resistance in Head and Neck Squamous Cell Carcinoma.

Acylation modification plays a crucial role in modulating head and neck squamous cell carcinoma (HNSCC) progression, and their specific prognostic imp...

Computed Tomography-Pathology Deep Learning Model for the Precise Prediction of Recurrence in Pathological Stage IA Lung Adenocarcinoma.

BACKGROUND: The postoperative prognosis of pathological stage IA lung adenocarcinoma (LUAD) exhibits significant heterogeneity. While the tumor node m...

MGML: A plug-and-play meta-guided multi-modal learning framework for incomplete multimodal brain tumor segmentation.

Leveraging multimodal information from Magnetic Resonance Imaging (MRI) plays a vital role in lesion segmentation, especially for brain tumors. Howeve...

Development and external validation of an MRI radiomics-based machine learning model to predict tumour recurrence in brain metastases treated with Gamma Knife radiosurgery.

BACKGROUND: Predicting recurrence after gamma knife radiosurgery (GKRS) is clinically important, as it informs salvage treatment and patient managemen...

Urinary Tumor DNA to Identify Candidates for Repeat Transurethral Resection in Non-Muscle-Invasive Bladder Cancer.

Repeat transurethral resection of bladder tumor (re-TURBT) is commonly recommended for patients with non-muscle-invasive bladder cancer (NMIBC) with h...

A multicenter multimodel habitat radiomics model for predicting immunotherapy response in advanced NSCLC.

A robust predictive biomarker is critical for identifying patients with NSCLC who may benefit from immunotherapy. This study developed a CT-based habi...

Metal-based nanomaterials achieve tumor treatment strategies by overcoming the blood-brain barrier of glioma and responding to the tumor microenvironment.

Glioblastoma (GBM) continues to be the most lethal form of primary brain tumor. Therapeutic efficacy is significantly hindered by the presence of the ...

Microrobots/micromotors in cancer therapeutics, advances and applications.

Cancer remains one of the most challenging diseases to conquer due to its high mortality rate and the lack of effective diagnostic and therapeutic too...

Integrative analysis of single-cell and bulk transcriptomes reveals metabolic heterogeneity and identifies PFKP as a therapeutic target in cervical cancer.

Cervical cancer (CC) is still a major gynecological tumor among women globally. The heterogeneity landscape and prognostic value of metabolic reprogra...

Visceral Adipose Tissue Alters Podometrics and Renal Compensation After Uninephrectomy.

INTRODUCTION: Obesity is an established risk factor for chronic kidney disease (CKD). However, excess visceral adipose tissue (VAT) termed visceral ob...

Automated Lymph Node and Extranodal Extension Assessment Improves Risk Stratification in Oropharyngeal Carcinoma.

PURPOSE: Extranodal extension (ENE) is a biomarker in oropharyngeal carcinoma (OPC) but can only be diagnosed via surgical pathology. We applied an au...

From diagnosis and treatment to prognosis: Clinical prospects of artificial intelligence in multimodal research of hepatocellular carcinoma.

PURPOSE: This review aims to critically evaluate the evolving role and clinical readiness of multimodal Artificial Intelligence (AI) in Hepatocellular...