Tianjin Medical University Cancer Institute and Hospital

Our objective was to assess the perioperative quality of life (QoL) of patients with pancreatic cancer (PC) and accurately capture the complex interactions and causal pointers that contribute to fluctuations. This longitudinal study (October 2024 to March 2025) assessed QoL in patients with PC undergoing potentially curative surgery at four stages: the day of admission (T1), 3-5 days postoperatively (T2), the day of discharge (T3), and 1 month postoperatively (T4). Analysis of variance and cross-lagged panel network (CLPN) analyzed stage differences and dynamic interactions, and centrality calculations mapped important intervention targets between stages. Among 277 analyzed patients (89.64% response rate from 309 approached), 66.79% had ductal adenocarcinoma; the remaining cases comprised pancreatic neuroendocrine tumors (11.91%), invasive intraductal papillary mucinous neoplasms (7.58%), solid pseudopapillary tumors (5.42%), and other types (8.3%). QoL differed significantly between stages (P < 0.001). Dimension scores for functioning and global health status declined before gradually improving, whereas symptoms followed an inverse pattern. Nodes with higher bridge-expected influence, out-expected influence, or in-expected influence in each CLPN were targets for clinical care (mainly pain and nausea and vomiting in T1→T2, pain and social functioning in T2→T3, and fatigue and financial difficulties in T3→T4). The accuracy and stability of the CLPN were verified as acceptable. The CLPN could precisely identify the interactions and causal connections among QoL dimensions across different stages. It provides anticipatory and prospective guidance for clinical healthcare professionals to enhance holistic care outcomes through early intervention on vital targets that impede dysfunction and symptom exacerbation.

Cyclin L1 (CCNL1) is highly expressed in multiple cancer types and has been linked to poor prognosis. However, the expression pattern of CCNL1 in breast cancer and its specific role in regulating breast cancer progression remain largely unknown. This study used cell and molecular biology techniques to examine how CCNL1 regulates the proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) of breast cancer cells. The applied methods encompassed plasmid transfection, Transwell assay, wound-healing assay, Western blot analysis, co-immunoprecipitation (Co-IP), and rescue assay. For the analysis of CCNL1-related factors and pathways, bioinformatics platforms including Metascape and HURI were also employed. CCNL1 is highly expressed in breast cancer cells and is associated with a poor prognosis. CCNL1 overexpression increased breast cancer cell invasion and migration and accelerated proliferation. Overexpression of CCNL1 was found to upregulate the mesenchymal marker Vimentin and downregulate the epithelial marker E-cadherin expression. There is close relationship between CCNL1, the NF-κB and PI3K/AKT signaling pathways. The direct interaction is verified between CCNL1 and DVL3 by Co-IP, indicating a negative correlation between the two proteins. CCNL1 overexpression affects breast cancer cells' paclitaxel sensitivity through the PI3K/AKT pathway. CCNL1 activates the NF-κB signaling pathway through its interaction with DVL3; additionally, it promotes the PI3K/AKT pathway. Together, these two mechanisms enable CCNL1 to exert a regulatory role in the progression of breast cancer.

Lung adenocarcinoma (LUAD) is a major subtype of lung cancer that frequently develops brain metastases. Tumor heterogeneity substantially complicates disease management, and reliable biomarkers for metastatic progression remain lacking. LIM domain kinase 1 (LIMK1), a key regulator of cytoskeletal dynamics, has been implicated in tumor progression; however, its role in regulating brain metastasis in LUAD remains unclear. Single-cell RNA sequencing data from 11 primary LUAD tumors and 10 brain metastases were analyzed to identify malignant epithelial subclusters associated with metastatic dissemination. Tumor evolutionary trajectories and gene regulatory networks were explored using pseudotime trajectory analysis and weighted gene co-expression network analysis. LIMK1 expression was validated using The Cancer Genome Atlas dataset, as well as RT–qPCR and Western blotting in LUAD tissues and cell lines. Functional assays, including cell proliferation, colony formation, migration, and invasion, were performed following LIMK1 knockdown in LUAD cell lines. Six malignant epithelial subclusters were identified, among which clusters 0 and 4 were significantly enriched in brain metastases and associated with poor survival outcomes. LIMK1 was identified as a hub gene within these metastasis-associated clusters. LIMK1 expression was markedly upregulated in LUAD tissues and cell lines, and elevated LIMK1 levels predicted an unfavorable prognosis. Functional experiments demonstrated that LIMK1 depletion significantly inhibited tumor cell proliferation, migration, and invasion, while partially reversing epithelial–mesenchymal transition (EMT). Mechanistically, LIMK1 was found to promote LUAD progression through activation of the PI3K/AKT/mTOR signaling pathway. LIMK1 represents a novel prognostic biomarker and metastasis-associated regulator in LUAD. By driving EMT and activating PI3K/AKT/mTOR signaling, LIMK1 facilitates malignant progression, highlighting its potential as a therapeutic target for LUAD patients with brain metastases.

Patients with peripheral T cell lymphoma (PTCL) who achieved tumor response with first-line standard therapy were at high risk of disease relapse. We explored golidocitinib (150 mg once daily) as maintenance therapy for this group of patients (JACKPOT26, NCT06511869). This study included two cohorts: patients achieving a complete response (Cohort 1 (CR), N = 30) and a partial response (Cohort 2 (PR), N = 18) during induction stage. All enrolled patients were transplant ineligible or did not have a transplant plan. All dosed patients were included in the efficacy and safety analysis. In Cohort 1, the 24-month disease free survival (DFS) rate was 74.2% with golidocitinib treatment. In nodal subtypes (AITL, NOS, ALK- ALCL), the 24-month DFS rate was 62.7%. In Cohort 2, median progression free survival (PFS) was 17.4 months, and 24-month PFS rate was 48.6%. Nine out of 18 patients with initial PR achieved complete response, leading to a complete response rate of 50.0%, and median duration of response of 23.9 months. The most common ≥grade 3 treatment-related treatment-emergent adverse events (TRAEs) were hematological adverse events in nature, including neutrophil count decreased (47.9%), white blood cell count decreased (31.3%), lymphocyte count decreased (14.6%) and leukopenia (12.5%). The majority of these TRAEs were reversible and clinically manageable. TRAEs leading to treatment interruption and discontinuation occurred in 60.4% and 10% of patients, respectively. No TRAEs leading to fatal outcomes were reported. This study suggests the potential of golidocitinib as maintenance therapy for patients with PTCL.

Abstract Leptomeningeal metastasis (LM) is a devastating complication of lung adenocarcinoma, the current diagnosis of which relies on invasive cerebrospinal fluid cytology or costly MRI, both of which are limited in sensitivity and accessibility. To enable early, noninvasive LM risk prediction, we developed a 2.5D delta-radiomics deep learning framework based on routinely acquired contrast-enhanced CT scans. The proposed architecture integrates multi-instance learning to aggregate slice-level features into patient-level representations while preserving spatial context and controlling computational complexity. Delta features, derived by comparing pre-LM and post-LM scans, quantified subtle longitudinal changes within intratumoral and peritumoral regions. Multiple classifiers were evaluated, with XGBoost selected for its optimal performance, and Grad-CAM visualization was employed to assess spatial attention, revealing biologically plausible regions that drove model predictions. A nomogram was constructed to facilitate individualized clinical application, and decision curve analysis (DCA) demonstrated a consistent net benefit across a broad range of decision thresholds. In the test set, the delta-based multi-instance learning signature (MILDelta) achieved an AUC of 0.871, outperforming models trained solely on pre-LM (AUC 0.574) or post-LM (AUC 0.661) images, whereas a combined model incorporating imaging signatures and clinical variables, including EGFR mutation status, yielded the highest predictive accuracy, with an AUC of 0.910. This interpretable delta-informed model leverages standard contrast-enhanced CT to achieve individualized, noninvasive LM risk stratification with demonstrated generalizability and clinical utility, offering a scalable tool for timely intervention in precision oncology workflows.

Background and Objectives: Emphysema and coronary artery calcium (CAC) share common lifestyle-related risk factors, yet their association in Chinese populations remains understudied. This study investigated how lifestyle factors influence the association between emphysema and CAC score in an urban Chinese general population. Methods: The study included 1000 participants from the Chinese Nelcin-B3 urban general population study originating in 2017 who underwent low-dose CT (LDCT) screening and comprehensive CT assessment. Emphysema was visually assessed by subtype and severity. CAC was measured using the Agatston method and categorized as 0, 1-100, and >100. Questionnaire-based lifestyle factors (smoking, BMI, diet, physical activity, alcohol consumption and environmental exposures) were categorized based on number of unfavorable behaviors. Multivariable multinomial logistic regression adjusted for age, sex, education and cardiovascular risk factors examined the associations between emphysema and CAC, with interactions and stratified analyses for lifestyle effects. Results: Emphysema was present in 62.3% of the participants, with centrilobular being the most common subtype (61.5%). Paraseptal emphysema was associated with both CAC 1-100 (OR: 2.07 [1.03-4.15]) and CAC > 100 (OR: 2.94 [1.26-6.84]). Severe emphysema was linked to CAC > 100 (OR: 3.50 [1.38-8.84]). These associations were stronger in the intermediate unhealthy lifestyle group for paraseptal (OR: 5.41 [1.70-17.22] and moderate and severe emphysema (OR: 9.64 [1.64-56.55]; OR: 3.73 [1.07-13.06]), respectively, but not significantly different. Conclusions: While paraseptal and severe emphysema are associated with higher CAC scores, there is no modifying effect of lifestyle factors. These findings suggest that cardiovascular risk assessment could be of importance in individuals with emphysema. Further longitudinal studies are needed to clarify the clinical implications.