Other Cancers

Harnessing lipid-driven immunometabolic pathways in omental metastases to enhance immunotherapy in patients with ovarian cancer.

Immunotherapy with immune checkpoint blockade (ICB) in epithelial ovarian carcinoma (EOC) shows limited clinical benefit only for a small subset of patients. Overall response rates are low, so that overcoming immunotherapy resistance and improved stratification are key. In this study, we investigated the immunometabolic landscape of EOC with a focus on omental metastases, identifying lipid-laden m...

Performance of deep learning-based segmentation of soft tissue sarcoma by MRI sequence, tumor type and location.

OBJECTIVE: Soft tissue sarcomas (STS) are a rare and heterogeneous group of tumors that pose a significant challenge for surgical planning. This study evaluated the performance of a deep learning model for automated STS segmentation on preoperative MRI, focusing on how different MRI sequences, anatomical locations, and histological subtypes influence model accuracy. MATERIALS AND METHODS: We retro...

Early electrocardiographic repolarization changes are associated with subclinical cancer therapy-related cardiac dysfunction in lymphoma patients: A machine learning-assisted longitudinal study.

UNLABELLED: Anthracycline-induced cardiotoxicity remains a significant clinical challenge. We evaluated longitudinal electrocardiographic (ECG) repola...

Neoadjuvant Systemic Therapy in Kidney and Bladder Cancer: Current Evidence and Emerging Paradigms.

Neoadjuvant systemic therapy has emerged as a strategy to improve outcomes in high-risk localized genitourinary malignancies. In bladder cancer, neoad...

Integrating machine learning of bulk and single cell RNA data to characterize immune mechanism of m6A related mitophagy genes in malignant gastric cancer.

BACKGROUND AND OBJECTIVE: Gastric cancer is a heterogeneous and complicated epithelial cancers. Chronic H. pylori and EBV infection, as well as intest...

Development and validation of a multimodal deep learning model for early esophageal squamous neoplasia detection and invasion depth prediction.

Early detection of esophageal squamous cell carcinoma (ESCC) is critical for optimizing patient outcomes. Magnifying endoscopy and endoscopic ultrason...

Benzo[a]pyrene promotes gastric cancer progression via activation of the Correa cascade through modulation of the STAT3-TP53-MMP9 molecular axis.

To investigate the role of Benzo[a]pyrene (BaP) in driving the Correa cascade during gastric cancer development, we employed an integrated strategy co...

AI-based BRAIx risk score for the intermediate-term prediction of breast cancer: a population cohort study.

BACKGROUND: Artificial intelligence (AI)-based algorithms are being implemented in breast screening to detect breast cancers on mammographic images. W...

A Multiomic Liquid Biopsy for the Earlier Detection of Colorectal Cancer.

UNLABELLED: Timely diagnosis and intervention in colorectal cancer are critical to improving patient outcomes and limiting disease progression. Screen...

Tumor metrics imaging core labs: primer for radiologists.

Imaging biomarkers have emerged as increasingly important endpoints in cancer clinical trials. Incorporating tumor metric reads as part of routine cli...

Early recurrence prediction and risk stratification of hepatocellular carcinoma after transarterial chemoembolization achieving imaging complete response based on contrast-enhanced CT machine learning.

OBJECTIVES: To develop and validate machine learning (ML) models using clinical and contrast-enhanced CT (CECT) parameters to assess recurrence risk i...

Deep learning ensemble models for CT-based differentiation of malignant and benign sacral bone tumors: development and evaluation.

OBJECTIVE: Radiologists often face challenges in differentiating benign from malignant sacral bone lesions due to their similar imaging characteristic...

Revealing Sleep Dynamics with PCT-CRV: A Novel Approach for Automatic Sleep Staging and Tracking Transitions using PSG Signals.

Polysomnography (PSG)-based accurate sleep staging is essential to monitor sleep quality and sleep-related disorders. Despite previous attempts for im...

Influence of body composition on the efficacy of nivolumab plus ipilimumab for metastatic clear cell renal cell carcinoma.

BACKGROUND: Immune checkpoint inhibitor therapy (ICI) with nivolumab+ipilimumab is a first-line (1L) standard for metastatic clear cell renal cell car...

TCR sequencing in cancer immunology and immunotherapy: what, when, where, why, and how.

T-cell receptors (TCRs) are generated through somatic recombination of variable (V), diversity (D), and joining (J) gene segments, resulting in an ext...

A high density of T-cell lymphocytes and Tregs subset correlate to a worse survival in major salivary gland carcinomas.

Salivary gland carcinomas (SGC) are rare and heterogeneous tumors with limited therapeutic options in advanced stages. Recent evidence suggests a pote...

Clinical value of ultra-low-dose chest CT with deep learning image reconstruction in the detection and characterization of pulmonary nodules.

OBJECTIVE: To evaluate the clinical value of ultra-low-dose CT (ULDCT) with deep learning image reconstruction (DLIR) in the diagnosis of pulmonary no...

GSDME-mediated pyroptosis modulates the immunosuppressive microenvironment in lung adenocarcinoma.

Despite the increasing recognition of pyroptosis, particularly that involving GSDME, its precise impact on tumor prognosis and the immune microenviron...

Integration of circulating tumor DNA data enhances lung cancer prediction in patients with COPD.

Patients with chronic obstructive pulmonary disease (COPD) are at increased risk of lung cancer, and the identification of circulating tumor DNA (ctDN...

Circulating tumor cells (CTCs) enumeration and machine-learning based diagnostic biomarkers for breast cancer detection.

BACKGROUND: Circulating tumor cells (CTCs) are detectable in early-stage cancer and may enable early cancer detection. We evaluated a CTC-based assay ...