Langer's axillary arch (LAA) is a common muscular variant that may affect the assessment of axillary lymph nodes in breast cancer. We investigated whether the presence of the LAA had a meaningful clinical impact in a large cohort of Korean patients with breast cancer.

The medical records and imaging of 2,904 patients (2,953 cases) who underwent axillary surgery for breast cancer were reviewed. The presence of LAA was determined using chest computed tomography scans. The number of retrieved lymph nodes, the accuracy of axillary ultrasonography, and survival outcomes were compared between the LAA and non-LAA groups.

The LAA muscle was identified in 301 patients (10.2%). Preoperative ultrasound evaluation showed a lower specificity in the LAA group (77.9% vs. 83.6%, p = 0.031). Additionally, invasive disease-free survival (iDFS) was significantly worse in the 'LAA-positive patients' after adjusting for stage, histologic grade, and treatment (adjusted hazard ratio, 2.00; 95% confidence interval, 1.00-4.01; p = 0.048), with regional axillary recurrence being notably more frequent in patients with the LAA muscle (p = 0.005).

The presence of the LAA muscle was associated with reduced specificity on preoperative ultrasound. Patients with LAA muscle-associated tumors had worse iDFS, with regional axillary recurrence occurring more frequently. Recognition of the LAA muscle during axillary staging and surgery may improve nodal assessment accuracy and outcomes, especially in the era of axillary surgery de-escalation.

Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine carcinoma characterized by rapid progression and early metastasis. Despite recent therapeutic advances, including immune checkpoint inhibitors and emerging targeted agents, survival outcomes remain poor. Recent molecular insights have identified four transcription factor-driven subtypes-SCLC-A, SCLC-N, SCLC-P, and the inflamed subtype SCLC-I-providing a framework for precision and immunotherapy-based strategies. This review summarizes the evolving scope of imaging in SCLC and highlights emerging approaches that support personalized medicine. Conventional imaging with CT, MRI, and fluorine 18 fluorodeoxyglucose PET/CT remains essential for diagnosis, staging, and treatment response assessment. Semiquantitative, volume-based PET/CT metrics, such as metabolic tumor volume and total lesion glycolysis, correlate with tumor proliferation and provide stronger prognostic value than maximum standardized uptake value. Emerging imaging approaches, including radiomics, radiogenomics, and machine learning, may further enable noninvasive tumor characterization and outcome prediction. Recent advances in molecular imaging, including delta-like ligand 3- and somatostatin receptor-targeted immune-PET, represent key steps toward biomarker-guided and personalized therapy. Together, integration of structural, functional, and molecular imaging with biologic insights is expected to shape the next phase of precision oncology in this highly aggressive malignancy. Keywords: Lung, Imaging Modality, PET, MRI, Molecular Imaging, Oncology, Neoplasms-Primary, CT, MR Imaging, Diagnosis, PET/CT, Small Cell Lung Cancer, Radiogenomics, Machine Learning, Radiolabeled Tracer, Personalized Medicine Supplemental material is available for this article. © RSNA, 2026.

Conventional type-1 dendritic cells (cDC1) are the main mediators of crosspresentation of tumor antigens to CD8+ T cells and provide a context of costimulatory molecules and cytokines that lead to cytotoxic T lymphocyte (CTL) responses. We analyzed bulk RNA sequences from 7 key clinical trials testing checkpoint inhibitors across multiple cancer types. cDC1- and CD8-associated gene signatures were analyzed. Multiplex tissue immunofluorescence was used to quantify cDC1 in melanoma, urothelial cancer, and non-small-cell lung cancer (NSCLC) samples and assess cDC1 tissue neighborhoods. Melanoma samples were studied with Xenium spatial transcriptomics (ST) and one series of NSCLC was analyzed using GeoMX-DSP. Strong associations across tumor types were found between cDC1 and CD8+ T cell transcripts with clinical outcomes. As mechanistically expected, transcripts for the CCL4 and CCL5 chemokines and the growth factor FLT3-L showed associations with cDC1 abundance. Tissue immunofluorescence showed a strong correlation of cDC1 and CD8+ T cell infiltration with clinical benefit upon treatment with checkpoint inhibitors (CPIs). Moreover, short distance between cDC1 and CD8+ T cells was found to define tissue niches associated with favorable outcomes. ST revealed recent T cell activation within immune cDC1-rich niches. cDC1 abundance, which determines CD8+ T lymphocyte density and activation in tumor tissues across cancer types, is strongly associated with clinical response to CPI-based immunotherapies.

Integrative multiscale imaging bridges the gap between macroscopic organ structures and microscopic cellular processes, enabling holistic visualization of anatomy and function across scales. Photoacoustic imaging (PAI) leverages melanin's potent contrast for label-free melanoma detection, yet its potential in lung imaging, challenged by air-tissue acoustic impedance mismatch, remains unexplored for melanoma lung metastases (MLMs). We used hierarchical multiscale PAI, transitioning from whole-body macroscale to localized mesoscale and single-cell-resolution microscale. PAI also guided photoablation interventions in the first and second near-infrared windows, requiring only 10.4 pg intracellular melanin/cell. Bioinformatic analysis of human MLM tissues revealed perturbed signaling pathways compared with normal skin and lung tissues, accounting for dysfunctional melanogenesis to enable label-free PAI with high sensitivity and specificity. Malignant MLM lesions in living mice, resected mouse lungs, and human lungs were delineated with margins closely conforming to histology. The high sensitivity allowed visualization of low-cellularity microsatellite foci down to a few tens of cell clusters, with sufficient penetration in the lungs of mice and Bama minipigs. The multiscale imaging methodology streamlines a theranostic workflow and specifically identifies MLM burden in a progressive, label-free manner, which may aid real-time tumor ablation in the future.

Gallbladder cancer is one of the most aggressive malignancies in the biliary system, and there is currently no internationally recognized standardized treatment protocol. Reports on the management of rare pathological types of gallbladder cancer are particularly limited. We present 2 cases of gallbladder cancer with rare pathological subtypes and their diagnostic and therapeutic processes, aiming to further enhance clinicians' understanding of these uncommon entities.

This report describes 2 cases of gallbladder cancer, both presenting with abdominal discomfort, raising concerns about the nature of the lesion and effective treatment strategies.

Postoperative pathology confirmed one case as gallbladder sarcomatoid carcinoma and the other as gallbladder carcinosarcoma, both of which are clinically rare types.

Both patients underwent laparoscopic cholecystectomy at our institution, with subsequent pathological and immunohistochemical examination.

As of the end of follow-up (November 30, 2025), both patients recovered well postoperatively.

Rare types of gallbladder cancer lack specific clinical manifestations, making early screening difficult. Most patients are diagnosed at an advanced stage. Surgical intervention should be performed as early as possible upon discovery.

Breast cancer is a prevalent malignancy among women worldwide. Understanding its molecular mechanisms is crucial for prevention, early diagnosis, and treatment. Using a dataset of intraoperative radiotherapy (IORT) for breast cancer, we analyzed 21 breast tissue samples from patients who received IORT and 16 samples from those who did not. Principal component analysis was employed to reveal data structure, and differentially expressed genes (DEGs) were identified. We constructed a gene network using weighted gene co-expression network analysis and conducted functional enrichment analysis and gene set enrichment analysis. Immune infiltration analysis and protein-protein interaction network analysis were performed, resulting in gene expression heatmaps and Comparative Toxicogenomics Database analysis. Finally, regulatory microRNAs (miRNA) for core genes were predicted using miRNA prediction websites. A total of 2774 DEGs were identified. Principal component analysis demonstrated the differentiation between IORT and non-IORT samples. DEGs were enriched in key biological processes, such as T-cell receptor signaling, immunological synapse formation, and apoptosis. Gene set enrichment analysis validated the functional enrichment of DEGs. Weighted gene co-expression network analysis constructed 15 modules and identified hub genes. Protein-protein interaction network analysis revealed 4 core genes (CD2, CD3D, CD3G, and CD3E). miRNA prediction identified regulatory miRNAs for these core genes. Comparative Toxicogenomics Database analysis revealed that these core genes are associated with breast tumors and inflammation. Immune infiltration analysis showed a high proportion of Macrophages M0 and Macrophages M2 in the samples and revealed correlations between T cells and neutrophils. These findings suggest that the core genes may play key roles in the pathological changes and immune regulation of breast cancer tissues. CD2 and CD3D may serve as potential immune-related biomarkers for IORT in the treatment of breast cancer, influencing tissue pathological changes in breast cancer patients by regulating immune responses and cell signaling pathways.

Cancer remains one of the leading global health challenges, with lung cancer (LC), breast cancer (BC), and colorectal cancer (CRC) among the most prevalent and deadly malignancies. The intratumoral microbiota (IM), a distinct microbial ecosystem within tumor tissues, has recently emerged as a potential modulator of carcinogenesis, immune responses, and metastatic progression. However, comparative cross-cancer analyses remain limited. Therefore, this study aimed to compare the IM across these cancer types, with particular emphasis on distinguishing metastatic from non-metastatic malignancies, to identify tumor-specific microbial signatures with potential relevance for biomarker discovery, patient stratification, and microbiota-informed therapeutic strategies.

We performed 16S rRNA gene sequencing to profile the IM in formalin-fixed, paraffin-embedded (FFPE) samples from 20 BC patients, 20 CRC patients and 15 non-small cell lung cancer (NSCLC) patients.

BC samples exhibited the highest genus-level richness, whereas CRC samples showed significantly greater overall alpha diversity, consistent with the microbial complexity of the gut environment. NSCLC samples displayed the most balanced microbial distribution, as reflected by the highest Shannon index value. Stratification by metastatic status revealed distinct microbial signatures: 16 genera were exclusive to metastatic tumors and 49 to non-metastatic ones. In BC specifically, the class Clostridia and the family Burkholderiaceae were enriched in non-metastatic samples, accompanied by functional shifts in pantothenate and coenzyme A biosynthesis, lysine metabolism, and lipid A pathways. Microbial network analysis further revealed differences in ecological community structure and keystone taxa: Streptococcus spp. predominated as hubs in metastatic tumors, whereas Neisseria spp. were central in non-metastatic networks.

Overall, our findings highlight cancer-type and metastasis-specific microbial signatures, supporting a potential role for the IM in tumor progression and offering novel avenues for biomarker discovery and therapeutic targeting.

Ovarian cancer poses the greatest threat to survival among gynecologic cancers in women. Long non-coding RNAs (lncRNAs) have emerged as critical regulators in oncogenesis. The current study aimed to elucidate the function and regulatory mechanism of lncRNA KRT7-AS in ovarian cancer.

The clinical significance of KRT7-AS was evaluated through bioinformatics analysis of data from public repositories. KRT7-AS expression was examined by RT-qPCR and fluorescence in situ hybridization. The function analyses were conducted using assays for cell proliferation, migration, invasion, wound healing, and colony formation. Assessment of cell cycle and apoptosis was performed using flow cytometry. Mitochondrial membrane potential (MMP), reactive oxygen species (ROS), lipid peroxidation, and ferrous iron (Fe²⁺) levels were measured with specific kits. Tumor growth was assessed using a xenograft mouse model.

Patients exhibiting high KRT7-AS expression had a significantly lower survival rate. Functional assays demonstrated that KRT7-AS overexpression enhanced tumorigenic behaviors, including cell proliferation, invasion, and metastasis, whereas its knockdown suppressed these malignant phenotypes. KRT7-AS depletion induced ferroptosis, as indicated by increased MMP and ROS levels, and the accumulation of lipid peroxidation and Fe²⁺. In rescue experiments, the ferroptosis inhibitor ferrostatin-1 reversed the reduction in cell viability caused by KRT7-AS knockdown. Finally, in vivo studies showed that KRT7-AS knockdown inhibited tumor growth and modulated the expression of ferroptosis-related proteins by elevating ACSL4 and reducing GPX4.

These findings suggest that KRT7-AS has potential as a diagnostic biomarker for ovarian cancer. Targeting KRT7-AS to induce ferroptosis may represent a promising therapeutic strategy for suppressing ovarian cancer progression.

Pancreatic ductal adenocarcinoma (PDAC) is currently the third leading cancer-related cause of death worldwide and is forecasted to become the second leading cause in the United States by 2030. Despite the development of multimodal treatment regimens, 5-year overall survival remained as low as 12%. Several efforts have been made to account for different aspects of heterogeneous tumor biology in PDAC, aiming to enable treatment stratification of defined subtypes. Besides targeting specific mutations, the definition of molecular (transcriptional) subtypes has gained substantial interest regarding response prediction and treatment stratification. Despite numerous advances in the field of genomic, transcriptomic, and proteomic characterization, the identified biomarkers do not yet facilitate predicting treatment response sufficiently in patients in vivo. Considering the growing evidence on the impact of the tumor microenvironment (TME) and intratumoral heterogeneity (ITH) on treatment resistance, there is an unmet clinical need for preclinical cultivation models that allow for predicting treatment response based on individual biological criteria. This review discusses the current advances in such in vivo (patient-derived xenografts) and ex vivo (organoids, organotypic slice cultures, cancer-on-chip) models for treatment response prediction and stratification in PDAC, and their potential implications in clinical translation.

Breast cancer remains one of the most prevalent malignancies among women worldwide, and despite advances in therapy and treatment options, tumour relapse and metastasis remain major clinical challenges, largely driven by the breast cancer stem cells (BCSCs) niche that resists conventional treatments and regenerates tumours. In breast cancer, where approximately 30% of patients who initially respond to treatment ultimately relapse and die of metastatic disease, targeting BCSCs is critical for improving patient outcomes. Cyclin-dependent kinase inhibitor 1A/p21 (CDKN1A/p21) is a multifunctional protein that is known primarily for its role in regulating the cell cycle in response to DNA damage. However, in this study, we aimed to explore the role of CDKN1A/p21 in the survival and expansion of BCSCs.

We used three-dimensional in vitro models to assess the influence of CDKN1A/p21 expression on the survival of BCSCs both under basal conditions and after oxidative damage. Spatial transcriptomics analysis and chromatin immunoprecipitation-quantitative PCR (qPCR) were used to investigate the role of CDKN1A/p21 in the regulation and control of BCSC gene expression signatures.

We demonstrated that alterations in CDKN1A/p21 expression affect the ability of breast cancer cells to grow and survive after oxidative damage. Mechanistically, we found that CDKN1A/p21 directly binds to the promoter and regulates the expression of CD44, SPP1, and TMSB10, a combination gene signature that is associated with a greater probability of recurrence and metastasis in breast cancer patients.

We propose that changes in gene regulation mediated by CDKN1A/p21 possibly contribute to cancer stem cell survival after oxidative damage, thus making CDKN1A/p21 a promising target for future drug discovery projects aimed at addressing the issue of therapeutic resistance and breast cancer metastasis.