Oncology/Hematology

Targeting high-risk multiple myeloma genotypes with optimized anti-CD70 CAR-T cells.

Despite the success of BCMA-targeting CAR-Ts in multiple myeloma, patients with high-risk cytogenetic features still relapse most quickly and are in urgent need of additional therapeutic options. Here, we identify CD70, widely recognized as a favorable immunotherapy target in other cancers, as a specifically upregulated cell surface antigen in high-risk myeloma tumors. We use a structure-guided de...

Learning-Based Classification of B- and T-Cell Lymphoma on Histopathological Images: A Multicenter Study.

Lymphoma, a clonal malignancy from lymphocytes, includes diverse subtypes requiring distinct immunohistochemical stains for accurate diagnosis. Limited biopsy specimens often restrict the use of multiple stains, complicating diagnostic workflows. Lymphomas are typically classified into B-cell and T-cell types, each with specific markers. This study represents the first feasibility study in deployi...

Single-cell and spatial transcriptomics reveals an anti-tumor neutrophil subgroup in microwave thermochemotherapy-treated lip cancer.

Microwave thermochemotherapy (MTC) has been applied to treat lip squamous cell carcinoma (LSCC), but a deeper understanding of its therapeutic mechani...

Machine learning in ovarian cancer: a bibliometric and visual analysis from 2004 to 2024.

OBJECTIVE: Ovarian cancer (OC) is a common malignant tumor in women, with poor prognosis and high mortality rates. Early diagnosis, screening, and pro...

Sex differences in bladder cancer: understanding biological and clinical implications.

Bladder cancer (BC) remains a significant global health concern, with substantial sex and racial disparities in incidence, progression, and outcomes. ...

Insights into KMT2A rearrangements in acute myeloid leukemia: from molecular characteristics to targeted therapies.

Acute myeloid leukemia (AML) with KMT2A rearrangements (KMT2A-r) represents a highly aggressive and prognostically unfavorable subtype of leukemia, of...

Application of Hyperspectral Imaging and Machine Learning for Differential Diagnosis of Hashimoto's Thyroiditis and Papillary Thyroid Carcinoma.

BACKGROUND: Hashimoto's thyroiditis (HT) and papillary thyroid carcinoma (PTC) often share similar features, leading to frequent misdiagnoses. Hypersp...

Integrating Remote Symptom Monitoring, Person-Centered Analytics, and Artificial Intelligence to Advance Precision Health Symptom Science in Oncology.

OBJECTIVES: To summarize the relevance of remote symptom monitoring, person-centered statistical analyses, and artificial intelligence to precision he...

Prediction of Glomerular Filtration Rate Following Partial Nephrectomy for Localized Renal Cell Carcinoma with Different Machine Learning Techniques.

: Partial nephrectomy (PN) is the preferred option for treating localized cT1 renal cell carcinoma (RCC), as it preserves renal function in most patie...

Elucidating the Prognostic and Therapeutic Implications of Insulin Resistance Genes in Breast Cancer: A Machine Learning-Powered Analysis.

Breast cancer (BC) is among the most prevalent malignancies and remains the leading cause of cancer-related mortality in women worldwide. While prior ...

Explainable Machine Learning Identifies Factors for Dosage Compensation in Aneuploid Human Cancer Cells.

Aneuploidy, a hallmark of cancer, leads to widespread changes in chromosome copy number, altering the abundance of hundreds or thousands of proteins. ...

M-GNN: A Graph Neural Network Framework for Lung Cancer Detection Using Metabolomics and Heterogeneous Graph Modeling.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with early detection critical for improving survival rates, yet conventio...

Improving AI models for rare thyroid cancer subtype by text guided diffusion models.

Artificial intelligence applications in oncology imaging often struggle with diagnosing rare tumors. We identify significant gaps in detecting uncommo...

Effect of Cell-Cell Interaction on Single-Cell Behavior Revealed by a Deep Learning-Aided High-Throughput Addressable Single-Cell Coculture System.

Cell-cell interactions are crucial for understanding various physiological and pathological processes, yet conventional population-level methods fail ...

Artificial Intelligence-Guided Cancer Engineering for Tumor Normalization Executed by Tumor Lysosomal-Triggered Supramolecular Chiral Peptide.

Cancer engineering for tumor normalization offers a promising therapeutic strategy to reverse malignant cells and their supportive tumor microenvironm...

Active Learning-Based Prediction of Drug Combination Efficacy.

Combination therapy, which involves the use of multiple drugs, has emerged as a promising approach to cancer treatment. However, traditional combinati...

Machine Learning and Deep Learning in Oncologic Imaging: Potential Hurdles, Opportunities for Improvement, and Solutions-Abdominal Imagers' Perspective.

The applications of machine learning in clinical radiology practice and in particular oncologic imaging practice are steadily evolving. However, there...

Application of BOLDMRIbased radiomics in differentiating malignant from benign renal tumors.

OBJECTIVES: Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) is a kind of non-invasive MRI technology which reflects the tissue bloo...

Application of bacteria-mediated gene therapy in tumor treatment.

INTRODUCTION: Gene therapy refers to the use of vectors to introduce target genes into target cells to exert a therapeutic effect on tumors. As a new ...

Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework

Breast-conserving surgery (BCS) aims to completely remove malignant lesions while maximizing healthy tissue preservation. Intraoperative margin asse...