The most common type of kidney cancer is ccRCC (Clear Cell Renal Cell Carcinoma). Existing research has shown that when kidney cancer progresses from T2 to T3 or T4 stage, the treatment options and prognosis significantly differ. The aim of this study is to identify prognosis-related genes in ccRCC using single-cell data and Mendelian randomization analysis.

Single-cell RNA sequencing (scRNA-seq) data from six ccRCC patients (GSE156632) were analyzed in R. After quality control and normalization, cells were embedded, clustered, and annotated to define major cell types. Cell-cell signaling networks were inferred using CellChat. Stage-related co-expression programs were identified using high-dimensional weighted gene co-expression network analysis (hdWGCNA), and modules enriched in advanced disease were prioritized. To connect expression patterns with germline variation, we obtained expression quantitative trait loci (eQTL) summary statistics from the UK Biobank and performed two-sample Mendelian randomization using the ukb-b-1316 exposure dataset. For clinical validation, bulk RNA-seq and survival data from The Cancer Genome Atlas (TCGA) were incorporated, and candidate genes were evaluated using univariable Cox proportional hazards models.

hdWGCNA identified three modules, from which we selected 150 genes. eQTL combined with Mendelian randomization analysis revealed a potential causal relationship between RBP5, PRDX2, GTSF1, BSG, and COX14 and tumorigenesis. Further TCGA data analysis indicated that PRDX2 might serve as a protective factor in ccRCC, consistent with the Mendelian randomization results. Furthermore, its expression exhibited a gradual decline with tumor stage progression. Kaplan-Meier(KM) curves demonstrated better prognosis for patients with high PRDX2 expression. Cell communication analysis revealed more frequent communication between cells with reduced PRDX2 expression and vascular endothelial cells. Moreover, the experiments demonstrate that the migration and proliferation abilities of ccRCC cells are enhanced after knocking down PRDX2.

These results suggest that PRDX2 may play a role in the progression of ccRCC and could potentially serve as a prognostic factor and therapeutic target for ccRCC.

This study aimed to identify predictors of anastomotic leakage (AL), including Grade C AL, after rectal cancer surgery and to establish a risk prediction model for clinical risk stratification.

A retrospective study was conducted on rectal cancer patients who underwent anterior resection (AR) at Tianjin Medical University Cancer Institute and Hospital between November 2020 and November 2024. Clinicopathological variables were analyzed, and multivariable logistic regression was applied to construct predictive models for overall and Grade C anastomotic leakage.

A total of 901 rectal cancer patients were included, with an AL incidence of 8.9% (80/901) and Grade C AL occurring in 4.7% (42/901). Multivariable analysis identified postoperative numerical rating scale (NRS) pain score (OR = 9.556; 95% CI, 6.014-15.184; p < 0.001), neoadjuvant chemoradiotherapy (NACRT) (OR = 3.070; 95% CI, 1.525-6.182; p = 0.002), intersphincteric resection (ISR) (OR = 4.928; 95% CI, 1.340-18.126; p = 0.016), intestinal obstruction (OR = 2.926; 95% CI, 1.105-7.748; p = 0.031), tumor size (OR = 2.238; 95% CI, 1.239-4.042; p = 0.008), operative time (OR = 2.416; 95% CI, 1.092-5.349; p = 0.030), diverting stoma (OR = 0.124; 95% CI, 0.031-0.491; p = 0.003), and gender (female vs. male) (OR = 0.410; 95% CI, 0.220-0.765; p = 0.005) as independent predictors of overall AL. For Grade C AL, NRS pain score (OR = 6.563; 95% CI, 2.565-16.791; p < 0.001) and NACRT (OR = 7.534; 95% CI, 2.012-28.216; p = 0.003) were significant predictors. The nomogram demonstrated strong discrimination, with C-statistics of 0.872 for overall AL and 0.817 for Grade C AL. NRS pain score achieved the highest individual predictive performance (AUC = 0.812 for overall AL; 0.759 for Grade C AL). Combined models integrating NRS with other variables further improved accuracy (AUC = 0.856 for overall AL; 0.817 for Grade C AL). Calibration curves showed excellent agreement between predicted and observed outcomes.

We developed a risk prediction model for AL after rectal cancer surgery using preoperative, intraoperative, and early postoperative variables. The NRS pain score was the strongest predictor, and any unexplained rise in pain should raise suspicion of impending AL. This model offers a practical tool for early postoperative risk stratification and enhanced monitoring in high-risk patients.

Prostate cancer (PCa) is the most common malignant neoplasm of the urogenital system, with definitive diagnosis currently relying exclusively on prostate biopsy. Although the transperineal approach is associated with a lower incidence of perioperative complications, postoperative subcutaneous hematoma in the perineal region may be overlooked due to its anatomically concealed presentation, leading to delayed clinical attention. This report presents a case of extensive subcutaneous hematoma involving the lower abdomen and perineum following transperineal prostate biopsy in a patient diagnosed with PCa. Prompt management with prostatic artery angiography and superselective prostatic artery embolization, supplemented by endocrine therapy, resulted in rapid resolution of the hematoma. At three-month follow-up, tumor biomarkers remained stable, and key biochemical parameters had returned to pre-biopsy baseline levels, indicating favorable disease control and recovery.

This study aims to create a model that combines ultrasonography (US), magnetic resonance imaging (MRI) examination, and clinicopathological features to predict the axillary pathological complete response (pCR) of patients with breast cancer (BC) who receive neoadjuvant therapy (NAT).

This retrospective study included 600 patients with node-positive breast cancer who were eligible for enrollment (clinical stage cT1-4 and cN1-3) and received neoadjuvant therapy from January 2011 to January 2024. Before biopsy and neoadjuvant therapy, these patients underwent ultrasound (US) and MRI imaging of breast lesions and axillary lymph nodes (ALNs), and clinicopathological features were recorded before and after NAT. All imaging evaluations were independently performed by two experienced breast radiologists (with >10 years of experience), and discrepancies were resolved by consensus. Independent risk factors for predicting ALN status after NAT were identified by univariate and multivariate analyses. These independent risk factors were used for nomogram construction.

Univariate logistic regression analysis revealed that the maximum diameter of the breast lesions on MRI after NAT (p < 0.001), MRI ADC-value after NAT (p < 0.001), maximum and minimum diameter of the ALN on US after NAT (p < 0.001), the Ki67 level (p < 0.001), tumor grade 3 (p = 0.017), primary ALN stage cN 2 (p = 0.022), efficacy evaluation of the neoadjuvant therapy, pT stage, MP classification, HR, HER2, and the presence of the Hilum of the lymph gland were significantly associated with ALN pCR after NAT (p < 0.05). In the multivariate logistic regression analysis, ypT2 (p < 0.001), ypT3 (p = 0.007), HER2 (p < 0.001), response PR (p = 0.007), efficacy evaluation (SD/PD) (p = 0.010), and the presence of the Hilum of the lymph gland on US after NAT(p < 0.001) were considered independent predictors of ALN pCR after NAT. The area under the curve (AUC) of the nomogram was 0.934(95% CI: 0.913-0.960) in the training set and 0.908 (95% CI: 0.867-0.950) in the validation set, with a sensitivity of 82.0% and a specificity of 89.1% in the training set.

Our noninvasive model based on US, MRI, and clinicopathological features can help accurately identify patients with ALN pCR after NAT and prevent unnecessary axillary lymph node dissection (ALND).

A solid pseudopapillary neoplasm of the pancreas is a rare tumor accounting for 1-2% of exocrine pancreatic neoplasms and around 5% of cystic pancreatic lesions in adults. It predominantly affects young women and is usually diagnosed incidentally due to its non-specific clinical presentation. Although its exact cause is unclear, it is believed to originate from pluripotent cells of the genital ridges. We report the case of a 26-year-old female patient with an asymptomatic epigastric mass. An magnetic resonance scan revealed a large, heterogeneous lesion in the head of the pancreas, with no evidence of vascular invasion or metastasis. A cephalic duodenopancreatectomy was performed, achieving tumour-free margins with no lymphovascular or perineural involvement. The patient had a favourable postoperative recovery, with no recurrence after three years of follow-up. These neoplasms are diagnosed based on imaging studies, and complete surgical resection is the treatment of choice. Despite their low malignant potential, factors such as tumour size, capsular invasion, and cellular atypia may influence prognosis. This case highlights the importance of treatment in specialized centers to optimize oncological outcomes.

This report describes a 53-year-old woman admitted for evaluation of a space-occupying lesion in the ascending colon detected one year earlier and recent right lower quadrant pain. Initial colonoscopy revealed a 2.0 × 2.0 cm submucosal elevated lesion with surface ulceration near the ileocecal valve. Biopsy showed inflammatory mucosa with abundant mucin but no malignancy, and CT revealed no definite abnormalities. One year later, the lesion enlarged to 3.5 × 3.0 cm with increased ulceration. Endoscopic ultrasound (EUS) demonstrated a hypoechoic submucosal mass, and endoscopic submucosal dissection (ESD) was performed. During ESD, a jelly-like substance raised suspicion of a mucinous neoplasm, leading to laparoscopic resection of the ileocecal region and ascending colon. Pathology confirmed mucinous adenocarcinoma originating from the submucosal layer. This rare presentation differs from typical colorectal cancers that arise from the epithelial layer. The combined use of EUS, ESD, and laparoscopic surgery facilitated accurate diagnosis and effective treatment.

Castleman disease (CD) is a rare lymphoproliferative disorder categorized into unicentric and multicentric forms. The unicentric form usually manifests as a localized lymph node enlargement. Mesenteric involvement is rare and can mimic other intra-abdominal neoplasms such as gastrointestinal stromal tumors, lymphoma, or metastatic disease, making preoperative diagnosis difficult. The study aimed to systematically analyze published cases of mesenteric unicentric CD (UCD) and evaluate demographic trends, anatomical distribution, histopathological variants, tumor characteristics, treatment strategies, and clinical outcomes. A systematic review of individual case reports published between 1996 and 2026 was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The literature search was conducted using PubMed and Scopus as the primary databases. Reports describing mesenteric UCD were screened, and relevant details, including age, sex, lesion size, location, histopathology, and management, were extracted. Data were summarized using descriptive statistics and synthesized narratively. The mean age at diagnosis was 35.3 ± 17.9 years, and the mean lesion size was 5.51 ± 2.25 cm. The mesentery (unspecified) was the most frequently reported site (75.68%), followed by the small bowel mesentery (18.92%) and large bowel mesentery (5.41%). The prevalence of mesenteric UCD with a hyaline vascular variant was 64.86%, followed by plasma cell (21.62%) and mixed types (12.16%). In 1.35% of cases, histology was not specified. Complete surgical excision represented the primary therapeutic approach (60.81%) and was associated with favorable outcomes in most patients. For mesenteric UCD, surgical excision remains the cornerstone of treatment, offering an excellent prognosis. Early recognition and accurate histopathological diagnosis are essential to avoid misclassification and guide optimal management.

Primary myelofibrosis (MF) is characterized by MF, splenomegaly, and extramedullary hematopoiesis. MF initially presents with reticular fibers (RFs) and progresses to increased collagen fiber deposition in the advanced stages. Although recent clinical trials have adopted MF improvement as an evaluation criterion, current diagnostic methods rely primarily on qualitative assessments based on the presence or absence of reticular and collagen fibers. Therefore, detecting subtle changes during the early stages of MF can be challenging.

We developed a novel deep learning-based method for quantitatively evaluating MF by measuring RFs as an indicator. Unlike collagen fibers, RFs are detectable from the early stages of MF and increase as the disease progresses. Moreover, based on the hypothesis that splenic fibrosis progresses in parallel with MF, we applied this method to evaluate RFs in the spleen. Using these methods, we analyzed temporal changes in fibrosis, splenomegaly, and hematopoietic stem cell dynamics over time in two MF models: a drug-induced fibrosis model using romiplostim and a Jak2V617F gene-transformed mouse. Additionally, we examined correlations between our quantitative fibrosis measurements and clinical data, including MF grade and genetic mutations.

Our findings revealed that in Jak2V617F gene-transformed mice, splenomegaly and extramedullary hematopoiesis in the spleen occurred earlier than MF. Furthermore, the quantitative fibrosis method significantly correlated with MF grade in patients with myeloproliferative neoplasms and the JAK2V617F mutant allele burden.

Our novel deep learning-based method successfully captured temporal changes in bone marrow and spleen fibrosis and shows potential for clinical application.

The authors have confirmed clinical trial registration is not needed for this submission.

Pituitary neoplasms may expand the sella and invade into adjacent structures, including the sphenoid sinus and/or the clivus. Previously, sellar remodeling assisted with detecting these tumors prior to the creation of computed tomography and magnetic resonance imaging. This project aims to quantify efficacy for discerning clival osseous changes in patients with pituitary neuroendocrine tumors (PitNETs) when compared to controls using artificial intelligence and machine learning models.

Electronic health records were reviewed. Still images of standard bone window CT heads were captured and compared using supervised machine learning/convolutional neural network (CNN) models trained on three singular axis (axial, coronal, or sagittal) CT sequences of a manually segmented clivus bone for each patient (102 images from 34 functioning PitNETs, 240 images from 80 nonfunctioning PitNET, and 387 images from 129 normal patients).

Overall, accuracies were favorable for axial sequences: Model 1 (axial PitNET vs. normal, accuracy 81%) and Model 4 (axial non-functioning PitNET vs. functioning PitNET, accuracy 95%), and Model 7 (axial non-functioning PitNET vs. functioning PitNET vs. normal, accuracy 83%). This performance difference may be due to added benefit of bilateral and anterior-posterior image features on axial views. Although this bilaterality of information is also available in coronal views, models consistently performed poorly compared to sagittal and axial sequences.

To date, no reports have detailed use of a CNN to identify subtle osseous changes and potentially detect PitNETs based on CT bone windows alone. Our models produced average accuracies up to 81% in correct identification of PitNET vs. control and 95% correct identification of functioning vs. nonfunctioning PitNET. These findings serve as a proof-of-concept that CNNs, may be trained to provide acceptable levels of accuracy with CT imaging, a modality more readily available than MRI.

BreathBC is a multicenter prospective observational cohort study aimed at comparing metabolic profiles from exhaled breath of patients with breast cancer (BC) and malignancy-free controls. The study accounts for the novelty and complexity of breath analysis, with a particular emphasis on the standardization of each step in the process.

Women with primary BC without distant metastasis, women carriers of germline BRCA1/2 pathogenic variants and controls were consecutively recruited in two clinical independent cohorts and two technical validation cohorts. Breath samples were collected and linked to clinical breast status, personal, medical and lifestyle data that were retrieved using a questionnaire focused on factors potentially affecting breath analysis.

Among 1010 participants, a group of 846 subjects, compliant with criteria of recruitment and sampling of the study, were preliminarily characterized. The mean age was 61 years for patients with BC and 58 years for controls, with 71% of women in post-menopause. The control group included 48% of participants with benign disease. Hypertension was the main age-related morbidity observed in 28% of participants and 10% were smokers. Among patients with BC, 15% had in situ disease and 85% an invasive cancer whose sub-typing presented a high prevalence of luminal subtypes, in agreement with the consecutive recruitment.Future activities will be focused on data analysis of breathomics data and on technical enhancement of prototypes used for sampling and instrumental analysis.