Other Cancers

Integration of hierarchical clustering in hematologic biomarkers prediction for endocrine toxicity during immunotherapy in lung cancer patients.

Immune check-point inhibitors (ICIs) have outstandingly changed the treatment for lung cancer patients providing longer progression-free (PFS) and overall survival (OS). Immune-related adverse events (irAEs) counteract this success, and different biomarkers are broadly investigated to predict their appearance. Hematologic predictive biomarkers for irAEs are extensively studied to better prevent, m...

Integrating habitat-based radiomics, 3D deep learning, and clinical variables for detection of early-stage esophageal squamous cell carcinoma on noncontrast chest CT: A multicenter study.

RATIONALE AND OBJECTIVES: To develop and validate a Combined model integrating habitat-based sub-regional radiomics, 3D deep learning (DL) features, and clinical variables for the detection of early-stage esophageal squamous cell carcinoma (ESCC) on noncontrast chest CT. MATERIALS AND METHODS: In this retrospective multicenter study, the segmented esophageal region of interest was partitioned into...

Integrated spatially guided transcriptomics and multiplex imaging identify a high-risk CD163+/CD11c-subgroup in diffuse large B-cell lymphoma.

Emerging data identify infiltrating immune cells in diffuse large B‑cell lymphoma (DLBCL) as prognostic biomarkers with tentative implications for the...

AI-Driven Multi-Omics Integrated Applications Using Diverse Neural Networks for Breast Cancer Diagnostic Screening and Biomarker Discovery.

Breast cancer (BC) is a highly complex and heterogeneous malignancy and the most prevalent cancer among women worldwide. The diagnosis, prognosis, and...

Multimodal features and prognostic risk assessment in locally advanced gastric cancer patients following neoadjuvant therapy based on machine learning algorithms: a multicenter study.

BACKGROUND: Neoadjuvant therapy (NAT) is recommended for locally advanced gastric cancer (LAGC), but some patients respond poorly. We aimed to constru...

The transcriptional landscape in thyroid cancer: current status of circulating biomarkers and liquid biopsy approaches.

INTRODUCTION: Thyroid cancer is the most common endocrine malignancy, and despite advances in understanding its genomic drivers, significant challenge...

Overcoming Liquid Biopsy Barriers: Nucleic Acid Biosensors Integrating DNA Nanotechnology and CRISPR-Cas System for Cancer Precision Theranostics.

Liquid biopsy holds immense potential for the early detection of cancer, yet its clinical utility is hindered not by the lack of available tumor-assoc...

Integrative single-cell and machine learning analysis identifies a tumor doubling time-related prognostic signature and therapeutic targets in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) exhibits marked molecular heterogeneity and diverse clinical outcomes, partly influenced by ...

Single-cell and spatial transcriptomics reveal SUV39H1 as a master epigenetic driver of immunosuppressive niche and stemness in bladder cancer.

Bladder cancer (BC) exhibits profound molecular heterogeneity and a highly dynamic tumor microenvironment, posing major challenges for effective thera...

Self-sufficient killing of malignant tumors by an engineered cancer-selective gene circuit.

Gene therapies that selectively eliminate tumor cells within a heterogenous population remain an elusive goal in oncology, largely due to the difficul...

From binary senescence to state-resolved senotherapy in cancer: therapeutic windows from heterogeneity.

Tumor senescence is a durable cell-cycle arrest triggered by oncogenic signalling, DNA damage and therapeutic stress. Although senescence can restrain...

Predicting Malignant Transformation in Oral Epithelial Dysplasia: A Systematic Comparison of Artificial Intelligence-Based Risk Models and Pathologist-Based Microscopy.

BACKGROUND/AIMS: Risk prediction models (RPMs) based on histopathological analysis of oral epithelial dysplasia (OED) are increasingly used to stratif...

Deep learning-based assessment of HER2-ultralow expression in breast cancer: a multi-center validation study across primary and metastatic lesions.

Accurate assessment of human epidermal growth factor receptor 2 (HER2) expression is foundational for targeted therapy in breast cancer (BC). The rece...

Multiomics and artificial intelligence identify infection associated subtypes and prognostic signatures in hepatocellular carcinoma.

UNLABELLED: Hepatocellular carcinoma (HCC) remains a major global health burden with persistently high morbidity and mortality. Dysregulation of the t...

Personalized cancer vaccines: bridging immune-oncology and precision medicine for advanced therapeutics.

Despite advancements in therapeutic cancer vaccines, clinical translation has been hindered by limited efficacy, with Sipuleucel-T remaining the only ...

Overcoming therapeutic resistance in biliary tract cancer: from resistance mechanisms to dynamic precision oncology - a narrative review.

INTRODUCTION: Biliary tract cancer (BTC) is a biologically heterogeneous and highly aggressive malignancy with limited therapeutic options and poor su...

DEGRO consensus framework for undergraduate radiation therapy teaching in Germany: a white paper with integrated guidance on artificial intelligence in medical education.

BACKGROUND AND PURPOSE: Undergraduate medical education is increasingly competency-based, digital, and interprofessional in accordance with the Nation...

Identification and functional validation of lipid droplet-associated prognostic biomarkers in breast cancer via integrative multi-omics and machine learning approaches.

BACKGROUND: Lipid droplet (LD)-associated metabolic reprogramming plays a critical role in breast cancer progression and immune modulation, yet robust...

Preoperative PET/CT phenotype of gastric-type endocervical adenocarcinoma: integrated morphological, metabolic, serological, and explainable machine-learning analysis.

PURPOSE: Gastric-type endocervical adenocarcinoma (GAS) is an aggressive, non-HPV-associated cervical adenocarcinoma that is often difficult to recogn...

Utilizing machine learning to identify multimodal signatures for patients who would benefit from the addition of tremelimumab to durvalumab and chemotherapy (TRIDENT).

PURPOSE: POSEIDON (NCT03164616) was a randomized, open-label, multicenter phase 3 trial comparing first-line durvalumab with or without tremelimumab i...