Other Cancers

Leveraging data-driven risk-adapted surveillance strategies after disease progression in locally advanced rectal cancer.

BACKGROUND: Post-progression survival (PPS) is a critical endpoint in oncology, yet predictors of PPS and data-driven strategies for post-progression management in locally advanced rectal cancer (LARC) remain undefined. This study aimed to identify prognostic factors for PPS, develop a predictive tool, and formulate risk-adapted surveillance strategies based on conditional survival to optimize lon...

Label-free cervical cancer detection in tissue samples using Raman spectroscopy combined with machine learning technology.

Cervical cancer is one of the most common malignant tumors of the female reproductive tract, ranking fourth among all female malignancies. Currently, the primary method for diagnosing cervical cancer is histopathological examination, which mainly relies on hematoxylin and eosin (H&E) staining of tumor tissues to evaluate cellular and structural morphology. However, conventional H&E staining depend...

The application of artificial intelligence in adrenal imaging: current state of knowledge, challenges, and future directions.

Adrenal incidentalomas are frequently detected on abdominal imaging and require evaluation for malignancy and hormonal activity. Although most are ben...

Multidimensional analysis of tumour immune microenvironment in HCC: prognostic significance and implications for immunotherapy.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) and anti-angiogenic agents represents the standard first-line therapy for patients ...

Development of a predictive model for postoperative body mass index and diabetes outcomes after metabolic bariatric surgery: retrospective cohort study.

BACKGROUND: Predicting postoperative body mass index (BMI) trajectories and long-term type 2 diabetes (T2D) remission after bariatric surgery remains ...

A multimodal deepsurv approach: integrating radiomics and clinical factors for brain metastasis survival prediction.

PURPOSE: Predicting survival outcomes for brain metastasis (BM) patients is crucial for tailoring treatment strategies and improving patient managemen...

New approach methodologies (NAMs) for preclinical and translational evaluation of mRNA-lipid nanoparticle (LNP) therapeutics.

Messenger RNA-lipid nanoparticle (mRNA-LNP) therapeutics have emerged as a versatile drug modality, enabling in vivo protein expression for vaccines, ...

Face/off: phase-specific modeling of lineage plasticity using near-patient models in genitourinary cancers.

Lineage plasticity has emerged as a fundamental mechanism of adaptive therapy resistance in prostate and bladder cancers, enabling malignant cells to ...

Benchmarking Zero-Shot Generative Pre-Trained Transformer-Based Multimodal Large Language Models for Pressure Injury Staging.

OBJECTIVE: To benchmark zero-shot generative pre-trained transformer (GPT)-based multimodal large language models (MLLMs) for pressure injury (PI) sta...

Extending responsible artificial intelligence to palliative care: the irreversibility problem with algorithmic accountability.

A hybrid quantum-classical framework for MRI-based deep brain tumor segmentation and classification.

The characterization of brain tumors from magnetic resonance imaging (MRI) is crucial for diagnosis, treatment planning, and prognosis. But the analys...

Pan-cancer analysis of tissue-plasma genomic concordance reveals enhanced concordance with liver metastasis and plasma clonality as predictor of poorer overall survival.

Circulating tumor DNA (ctDNA) enables noninvasive tumor genotyping, yet its concordance with tissue remains unclear. Using a 437-gene panel in 1111 pa...

Targeting m6A-SCG2-TAMs axis overcomes 5-FU resistance in colorectal cancer via a multi-omics model.

Chemoresistance to 5-fluorouracil (5-FU) remains a critical barrier in colorectal cancer (CRC) management. This study integrates multi-omics data from...

Multi-omics and metabolic flux modeling reveal that macrophage CYP27A1-derived 26-hydroxycholesterol drives immunosuppression and cancer malignancy.

Emerging evidence indicates that aberrant cholesterol metabolism in macrophages plays a role in tumorigenesis, however, how specific metabolites relea...

A machine-learning-derived multi-cell death mode signature predicts melanoma prognosis and reveals an immune-cold tumor microenvironment.

BACKGROUND: Regulated cell death programs influence melanoma progression and antitumor immunity, yet a robust prognostic model integrating multiple ce...

Improving pancreatic adenocarcinoma prognosis models through ligand receptor interactions and histopathological integration.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) has an extremely poor prognosis, and existing prognostic markers fail to fully capture the complex hetero...

Single-session agreement of ChatGPT and Gemini treatment recommendations with multidisciplinary tumor board decisions in thoracic oncology.

BACKGROUND: To evaluate the single-session agreement between treatment recommendations generated by ChatGPT and Gemini and real-world decisions made b...

Leveraging multimodal cancer immunotherapy to amplify the efficacy of oncolytic viruses.

Oncolytic viruses (OVs) represent a versatile platform for cancer immunotherapy, capable of selectively infecting and lysing tumor cells while trigger...

Radiomics-Based AI for the Diagnosis and Prognosis of Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.

BACKGROUND: Vessels encapsulating tumor clusters (VETCs), a CD34-positive vascular pattern in hepatocellular carcinoma (HCC), are linked to aggressive...

High-sensitivity photoelectric sensing of apatinib for recurrent hepatocellular carcinoma in TACE.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, with transcatheter arterial chemoembolization (TACE) being a widel...