Oncology/Hematology

Machine learning-based cfDNA fragmentation profiling using automated capillary electrophoresis for early detection of hepatocellular carcinoma.

BACKGROUND: Early detection of hepatocellular carcinoma (HCC) remains a significant clinical challenge due to the limited sensitivity of current surveillance tools, alpha-fetoprotein (AFP) and ultrasound. Recently, cell-free DNA (cfDNA) fragmentation analysis has shown promise in cancer detection; however, current sequencing-based approaches remain costly and unsuitable for large-scale screening. ...

Germline Pathogenic Variant Prediction Model for Tumor-Only Sequencing Based on Japanese Clinicogenomic Database.

PURPOSE: Germline pathogenic variants (GPV) are frequently identified as secondary findings in cancer gene panel testing. Due to limited data on germline conversion rates (GCR) in the Japanese population, clinical decisions have relied on European Society for Medical Oncology (ESMO) criteria. We aimed to develop a variant-level GCR prediction algorithm using a Japanese tumor-normal matched panel d...

Nuclear medicine in predicting hepatocellular carcinoma response.

Immune checkpoint inhibitors and anti-angiogenic targeted therapies have improved outcomes in hepatocellular carcinoma (HCC), but responses remain het...

Multi-encoder U-Net benchmarking for LiTS17 Liver-Tumor segmentation: accuracy-efficiency trade-offs across training durations.

OBJECTIVES: Accurate liver and tumor segmentation from CT is fundamental for diagnosis, treatment planning, and longitudinal monitoring of liver cance...

Machine learning models classifiers enable a strong prediction of radioembolization-induced liver disease, and define a new bilirubin threshold for selection of patients.

PURPOSE: Selective Internal Radiotherapy (SIRT) is an established treatment option for hepatocellular carcinoma (HCC). However, a major complication i...

Radiomics for early detection of pancreatic cancer: a systematic review and meta-analysis.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the lethal malignancies, in which accurate and faster detection is required in high-risk...

Fragment-based drug design coupled with AI/ML prediction enables identification of novel PARP-1 inhibitors against triple-negative breast cancer.

Triple-negative breast cancer occurs as a formidable challenge in cancer research due to the characteristically aggressive behaviour, poor prognosis, ...

Predictors of sensitivity to immune therapies in classic Hodgkin lymphoma.

Immune checkpoint blockade, particularly programmed cell death protein 1 inhibition, has redefined the management of classic Hodgkin lymphoma (cHL), a...

Application of fractal theory in cancer detection: A review.

Fractal theory has emerged as a quantitative framework for characterizing the complex and heterogeneous architecture of cancerous tissues; however, it...

Coordinated DNA methyltransferase 3A and methyltransferase-like 7A activity reprograms the tumor microenvironment through discoidin domain receptor 1 signaling.

OBJECTIVE: Breast cancer is the most common malignancy in women and is characterized by a high recurrence rate that severely impacts patient survival....

Comparable survival after lobectomy and total thyroidectomy for T3b differentiated thyroid carcinoma: A population-based study.

BACKGROUND: The 2025 American Thyroid Association guidelines recommend total thyroidectomy for all T3b differentiated thyroid carcinoma (DTC). However...

Recent Advances in Cancer Diagnostics: Exotic Animal Medicine and Beyond.

Recent advances in veterinary diagnostic oncology have significantly improved neoplasia detection in animals, including zoo, exotic, and wildlife spec...

Advancements and challenges in CAR-NK cell therapy for cancer treatment.

Chimeric antigen receptor natural killer (CAR-NK) cell therapy is an emerging cancer treatment offering advantages over CAR-T therapy, including reduc...

Exploratory identification of COL1A1 as a potential gene linking endocrine-disrupting chemicals and lung adenocarcinoma: a bioinformatics and machine learning analysis.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are common environmental pollutants that affect human health. These chemicals have been linked to th...

FCRLB-mediated dual control of tumor metabolism and macrophage polarization promotes lung cancer malignancy.

Harnessing artificial intelligence in gastrointestinal endoscopy for early detection of dysplastic lesions in inflammatory bowel disease.

Artificial intelligence (AI) has become an increasingly valuable tool in gastrointestinal endoscopy, especially in the context of inflammatory bowel d...

Deep-Learning Tool ScVital Enables Species-Agnostic Integration of Cancer Cell States.

UNLABELLED: Genetically engineered mouse models (GEMM) of cancer are useful for exploring the development and biological composition of human tumors. ...

CanSig Benchmarks Methods for Reproducible Cancer Cell State Discovery from Single-Cell Transcriptomic Data.

UNLABELLED: Single-cell RNA sequencing facilitates the discovery of gene expression signatures that define cell states across patients, which could be...

Practical Trade-Offs in 3D Cancer Imaging.

Three-dimensional (3D) imaging is increasingly shaping cancer research. This piece highlights key technical considerations when adopting 3D over tradi...

Title: AI-based quantification of tumor-infiltrating lymphocytes with integrative transcriptomics in ovarian clear cell carcinoma: JGOG3025-TR1/A1 study.

Transcriptomic classification methods have been proposed for ovarian clear cell carcinoma. However, their clinical significance and association with p...