Clinical Cancer Research

BackgroundIn immune checkpoint inhibitor (ICI) trials, overall survival (OS) benefits are well established, yet improvements in quality of life (QoL) are often inconsistent or absent in conventional analyses. This apparent discordance raises important questions: are QoL outcomes truly unrelated to survival, and how can QoL results be better utilized and interpreted? MethodsA model-based meta-analysis (MBMA) of longitudinal EORTC QLQ-C30 global health status/quality of life data from randomized ...

Multi-cancer early detection (MCED) tests can detect several cancer types and stages. We previously developed a methylation and protein (MP V1) MCED classifier. In this study, we present a refined MP V2 classifier, developed by evaluating model architectures that improved performance in prospectively enrolled case-control cohorts under standard testing conditions. The newly developed MP V2 classifier was trained to be more generalizable and achieve increased early-stage sensitivity at a target s...

BackgroundThe management of residual axillary disease after neoadjuvant therapy (NAT) remains controversial, as current recommendations often treat ypN1 breast cancer as a homogeneous entity despite potential prognostic heterogeneity. Evidence supporting uniform axillary surgical strategies across different levels of residual nodal burden is limited. We investigated whether survival associations related to axillary surgical evaluation differ according to residual nodal burden in ypN1 disease, us...

Clear cell renal cell carcinoma (ccRCC) is the leading cause of kidney cancer-related death, but how the tumor microenvironment shapes patient survival is not completely understood. Here, we describe the characterization of ccRCC tumor ecosystems from 498 patients using imaging mass cytometry with a focus on tumor, myeloid, and T cell landscapes. Data from more than 3 million single cells is analyzed using machine-learning to identify key ecosystem features that outperform basic clinical data fo...

Molecular subtyping of cancer is traditionally defined in transcriptomic space, yet routine clinical deployment is limited by the availability and cost of sequencing. Meanwhile, histopathology captures rich morphological information that is known to correlate with molecular state but lacks a principled, mechanistic bridge to gene-level representations. We propose a graph-constrained learning framework that aligns morphology-derived signals with a fixed, data-driven gene network discovered via hi...

Introduction: Manual data extraction from unstructured clinical notes is labor-intensive and impractical for large-scale clinical and research operations. Existing automated approaches typically require large language models, dedicated computational infrastructure, and/or task-specific fine-tuning that depends on curated data. The objective of this study is to enable accurate extraction with smaller locally deployed models using a disease-site specific pipeline and prompt configuration that are ...

Purpose: Tumor genomic testing (TGT) is standard-of-care for most patients with advanced/metastatic cancer. Despite established guidelines, patient education prior to TGT is frequently omitted. The purpose of this study was to evaluate the impact and durability of a concise 3-4 minute video for patient education prior to TGT in community versus academic sites and across cancer types. Patients and Methods: Patients undergoing standard-of-care TGT were enrolled at a tertiary academic institution ...

A recent randomized clinical trial in non-small cell lung cancer1 confirms what numerous observational studies have reported time of day (ToD) may dramatically influence treatment outcomes in cancer patients. In this recent trial median overall survival (OS) decreased from 28 months in the early ToD arm to 16.8 months in the late ToD arm. We raise the concern that clinical trial outcomes may be influenced by seemingly minor biases in treatment time across arms. We also suggest that by measuring ...

Immune effector cell-associated neurotoxicity syndrome (ICANS) is a common and life-threatening complication of chimeric antigen receptor (CAR) T-cell therapy, with early detection being critical for timely intervention and improved outcomes. Cytokines such as interleukin-6 (IL-6) are key mediators of the inflammatory cascade underlying ICANS pathogenesis, but prospective clinical evidence for their predictive value is limited. Here we quantify IL-6 levels in a prospective cohort of 40 CAR-T pat...

Abstract Background: Conventional MRI cannot reliably distinguish radiation necrosis (RN) from recurrent metastasis after cranial radiotherapy, as both can show similar enhancement despite different biology. We tested whether these entities are mechanically non-equivalent in vivo and separable by MRE-derived viscoelastic metrics and perilesional interface-instability features. Methods: In a prospective, histopathology-anchored cohort, 11 post-radiotherapy enhancing lesions were classified as RN ...

Importance: Lung cancer mortality in the United States has fallen substantially in recent decades, yet the relative influence of behavioral, environmental, socioeconomic, and therapeutic factors and their sex specific contributions remains unclear. Understanding these drivers is essential to sustain progress and reduce persistent disparities. Objective: To quantify how behavioral, environmental, socioeconomic, and therapeutic determinants collectively shaped US lung cancer mortality from 1994 to...

Digital breast tomosynthesis (DBT) is a powerful imaging modality that allows for improved lesion visibility, characterization, and localization compared to conventional two-dimensional digital mammography. DBT has been increasingly adopted in screening and diagnostic settings globally, particularly for women with dense breast tissue where tissue overlap presents a significant diagnostic challenge. Here we describe DBT-2026, a real world imaging dataset with 558 DBT exams from 558 patients with ...

A critical challenge in endocrine neurosurgery is intraoperative discrimination between normal pituitary tissue and pituitary neuroendocrine tumors (PitNETs). Suggesting the universal persistence of near-infrared autofluorescence (NIRAF) in endocrine organs and inspired by routine clinical use of NIRAF for parathyroid gland identification, we discovered that pituitary NIRAF can be employed for label-free transsphenoidal surgery guidance. Ex vivo confocal spectral imaging of 33 specimens identifi...

We propose a lesion-centric phenotype learning pipeline for interpretable breast ultrasound (BUS). Predicted lesion masks are used for mask-weighted pooling of segmentation-encoder latents, producing compact embeddings that suppress background influence; a lightweight calibration step improves cross-dataset consistency. We cluster embeddings to discover latent phenotypes and relate phenotype structure to morphology descriptors (compactness, boundary sharpness). On BUSI and BUS-UCLM with external...

Tumour typing from whole-genome sequencing is increasingly accurate, yet molecular subtyping from somatic variants remains challenging because of tumour heterogeneity and inconsistent clinical annotations. Here, we present Mutation-Attention Dual-Task (MuAt2), a Transformer model that jointly classifies histological tumour types and subtypes directly from somatic single-nucleotide variants, indels and structural variants. MuAt2 leverages encoders pre-trained on 2,587 pan-cancer whole genomes, an...

Background and Purpose: Magnetic resonance imaging (MRI) for radiation therapy treatment planning is currently being used in many anatomical sites to better visualize soft tissue landmarks, a technique known as an MRI simulation. A core component of modern MRI simulation configurations are the use of external laser positioning systems (ELPS) to help set up the patient. Though necessary for accurate and reproducible patient setup, the ELPS, if left on during imaging, may interfere negatively with...

3D-DXA reconstructs DXA hip scans to 3-dimensional images allowing measurement of trabecular and cortical bone parameters. Given the higher image quality of GE Healthcare iDXA than GE Healthcare Prodigy, it could be hypothesized that the reconstruction might differ, thereby affecting 3D-DXA results. The aim of the study was to assess agreement and precision of 3D-DXA cortical and trabecular femur parameters between Prodigy and iDXA densitometers in adult subjects. The study cohort was composed o...

Handheld ultrasound devices have revolutionized point-of-care diagnostics, but their effectiveness remains limited by operator dependency and the need for specialized training. This paper presents an intelligent guidance and diagnostic assistance system for the handheld wireless ultrasound device, enabling automated carotid artery and thyroid examinations through handheld operation. Drawing inspiration from the Actor-Critic framework, we implement a simulation-based reinforcement learning approa...

Accurate polyp segmentation from colonoscopy images is critical for colorectal cancer prevention, yet the generalization of deep learning models under domain shift remains insufficiently explored. We propose Boundary-Explicit Guided Attention U-Net (BEGA-UNet), a boundary-aware segmentation architecture that introduces explicit edge modeling as a structural inductive bias to enhance both segmentation accuracy and cross-domain robustness. The framework integrates three components: an Edge-Guided ...

The use of semaglutide (SE), a glucagon-like peptide-1 receptor agonist (GLP-1RA) with glucose-lowering and weight-loss effects, has risen rapidly, particularly among women of reproductive age. While preclinical studies suggest benefits for ovarian function via the hypothalamic-pituitary-ovarian axis, its impact on the endometrial-embryo interface remains unclear. Here, we show that GLP-1R is dynamically expressed in fertile human endometrium, restricted to epithelial cells and markedly upregula...