Breast Cancer

AI-predicted spatial transcriptomics unlocks breast cancer biomarkers from pathology.

Spatial transcriptomics (ST) assays are transforming our understanding of tumor heterogeneity, but their high cost limits their application in large-scale biomarker discovery. Here, we present "Path2Space," a deep-learning model that predicts spatial gene expression directly from histopathology slides. Trained on extensive breast cancer ST data, Path2Space robustly predicts the spatial expression ...

Machine learning-based integration of transcriptome and digital pathology for predicting chemoresistance in muscle-invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) presents with variable clinical and pathological features, leading to inconsistent responses to standard treatments such as neoadjuvant chemotherapy (NAC). Although transcriptome profiling has shown differences in NAC response, reliable predictors of treatment outcome remain elusive. Here this study aimed to improve NAC response prediction by integrating multi...

De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics.

Growth differentiation factor-15 (GDF15), a stress-responsive cytokine of the transforming growth factor-β superfamily, is elevated in cancer cachexia...

ELOVL1 promotes the progression of intrahepatic cholangiocarcinoma by enhancing endoplasmic reticulum stress and the PI3K/AKT/mTOR signaling pathway.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive liver malignancy characterized by an adverse outcome attributed to delayed d...

Emerging Therapeutic Paradigms in Tuberculosis: Nanocarriers, Host-Directed Strategies, and Translational Pharmacology.

TB remains a significant global health burden due to protracted therapeutic courses, poor patient compliance, and toxicities associated with drug trea...

Managing multidrug resistant Gram-negative bacteraemia in immunocompromised hosts.

PURPOSE OF REVIEW: Multidrug-resistant Gram-negative bloodstream infections (MDR-GNBSI) are increasingly frequent in immunocompromised hosts, particul...

Reconstruction algorithms and arm positioning effects on abdominal CT image quality and radiation dose: a phantom study.

OBJECTIVE: To evaluate the effects of arm positioning and reconstruction algorithms on radiation dose and image quality of abdominal CT. MATERIALS AND...

Pancreatic cancer.

Pancreatic ductal adenocarcinoma remains one of the deadliest malignancies, characterized by late diagnosis, aggressive biology and limited therapeuti...

An interpretable deep learning biomarker for prognostication and prediction of adjuvant chemotherapy benefit in gastric cancer.

Prognostic stratification in gastric cancer (GC) currently relies on the tumour-node-metastasis (TNM) staging system, which incompletely captures tumo...

Machine learning-based prognostic signature integrating mitochondrial function and programmed cell death patterns in pancreatic adenocarcinoma.

The interplay between mitochondria and programmed cell deaths (PCD) is associated with tumor pathogenesis. However, the specific roles of genes relate...

Integrating single-cell multi-omics and machine learning to reveal triaptosis heterogeneity in clear cell renal cell carcinoma.

Triaptosis, an emerging form of cell death, remains poorly characterized in terms of its heterogeneity within clear cell renal cell carcinoma (ccRCC)....

Machine learning enhanced optical spectroscopy for breast cancer diagnosis: A review.

This literature review examines the transformative role of machine learning (ML) and deep learning (DL) in enhancing optical spectroscopy for breast c...

Expanding the Therapeutic Window in Oncology: Modern Strategies and Future Directions.

Background:The enhancement of the therapeutic window (TW) in oncology remains a significant challenge, as the majority of anticancer treatments face d...

National Institute of Allergy and Infectious Diseases (NIAID) - Bundeswehr Institute of Radiobiology (BIR) Joint Programmatic Workshop on a Global Approach to Medical Countermeasure Development in Radiological Public Health Preparedness.

This invited commentary grew out of a presentation made at the 2025 ConRad Meeting in Munich, Germany, and summarizes talks made by researchers suppor...

Positron emission tomography imaging of inflammation and infection in children: an update.

Positron emission tomography (PET) has been used in pediatric oncology since the modality gained traction 20 years ago but has been used more sparingl...

Enabling DCIS subtyping: leveraging foundation models for robust grading and molecular biomarker scoring.

Ductal Carcinoma In Situ (DCIS) is a non-obligate precursor of invasive breast cancer. Due to a lack of reliable prognostic markers, nearly all women ...

Low-dose CT reconstruction by self-supervised learning in the projection domain.

OBJECTIVE: To address the critical issue of compromised image quality and diagnostic accuracy in low-dose computed tomography (LDCT) due to increased ...

Evidential reasoning-enabled deep learning for reliable treatment outcome prediction in cancer therapy.

Treatment outcome prediction plays an important role in realizing personalized cancer therapy. In triple-negative breast cancer (TNBC), neoadjuvant ch...

Non-small Cell Lung Cancer in Metastatic Renal Cell Carcinoma Patients.

INTRODUCTION: Renal cell carcinoma (RCC) most commonly metastasizes to the lungs and shares risk factors with lung cancer. However, primary lung cance...

Examination of Pathologist-Artificial Intelligence Interactions and Their Impact on Pathologist Accuracy Using Artificial Intelligence-Assisted Scoring of Immunohistochemistry for Human Epidermal Growth Factor Receptor 2.

CONTEXT.—: Advances in computer vision have fueled the development of artificial intelligence (AI)-based algorithms for pathology. AI-assisted approac...