Palbociclib is the more extensively evaluated CDK4-6 inhibitor in term of safety, efficacy and sources of pharmacokinetic variability. However, real-life data on the correlation between palbociclib plasma concentration, drug-drug interactions, gene polymorphisms and efficacy remain scarce. We previously characterized the effects of co-medications (CYP3A4 and P-glycoprotein inhibitors and antacid drugs) on palbociclib plasma concentration, and here we wanted to identify factors that influence progression-free survival in the same cohort of patients.

This multicentric prospective clinical trial included patients with metastatic breast cancer treated with first-line palbociclib and an aromatase inhibitor. Efficacy (progression-free survival) and safety (high-grade neutropenia during the first two cycles) were reported, and the influence of covariates, such as drug-drug interactions, palbociclib plasma concentration and specific gene variants, were analyzed.

In the 58 included patients, drug-drug interactions (antacid drugs) and pregnane X receptor (NR1I2) single nucleotide polymorphisms (SNP) were identified as survival prognostic factors, but not palbociclib concentration and high-grade neutropenia (p = 0.4 and p = 0.5). Concomitant antacid treatment reduced progression-free survival (26.2 vs. 32.6 months, p = 0.059) and the NR1I2 rs10934498 and rs2276707 SNPs affected survival (p = 0.002 and 0.004).

This study consolidated the data on palbociclib as first-line metastatic breast cancer treatment and identified factors that negatively influence survival (co-treatment with antacid drugs and NR1I2 SNPs).

NCT04025541, Registration Date 2019-07-16.

Immune checkpoint inhibitor (ICI)-induced cardiac immune-related adverse events (cardiac irAEs) are rare yet serious complications. Clinical assessment tools to identify at-risk patients would allow for more effective prevention strategies, thus improving clinical outcomes. We constructed various machine learning (ML) models to predict these events among patients receiving ICI therapy.

A cohort of patients receiving ICI therapy from 2010 to 2023 was identified from the TriNetX database. Cardiac irAEs were defined as the occurrence of relevant diagnosis codes within 90 days of ICI initiation, with corresponding hospital visits. We created ML models to predict these events, including elastic net logistic regression and multiple tree-based approaches (gradient boosted trees and random forest). We evaluated model performance with different performance measures and utilized assigned risk scores to stratify risk of cardiac irAEs into low, medium, and high-risk tiers.

We identified 61,117 patients receiving ICI therapy, with nearly 2% of patients experiencing cardiac irAEs. Model performance on testing data was comparable with all approaches (AUC = 0.71-0.72, balanced accuracy = 65-66%). Each model emphasized distinct features to make classifications, as observed with feature importance and SHAP values. Comparing cardiac irAE rates among assigned risk strata, patients identified as high risk were significantly more likely to experience cardiac irAEs compared to lower tiers.

Our preliminary exploration of ML methods demonstrated the potential for risk assessment tools to predict rare cardiac irAEs in patients receiving ICI therapy. Follow-up studies can implement time series approaches to harness longitudinal data that incorporates real-time labs, new diagnoses, and new therapy, to refine predictions further.

According to Chinese clinical practice guidelines, patients with hepatocellular carcinoma (HCC) at high risk of recurrence after curative hepatectomy should have adjuvant transcatheter arterial chemoembolisation (TACE). However, the National Comprehensive Cancer Network and the European Association for the Study of the Liver guidelines take a more conservative stance on the routine use of adjuvant TACE. A recent randomised controlled trial (RCT) found no benefit of adjuvant TACE for patients with early-stage HCC. Given the potential ethical concerns, it is impractical to conduct another RCT. Therefore, we plan to use a target trial emulation (TTE) framework to estimate the effectiveness and safety of adjuvant TACE in patients with resectable HCC, classified as Barcelona Clinic Liver Cancer stage 0-B, with subgroup analyses to identify potential effect-modifying subpopulations.

A TTE framework using the cloning-censoring-weighting approach with a 4-week grace period will be implemented. Eligible patients will be cloned into the adjuvant TACE and active surveillance groups and artificially censored on deviation from their assigned treatment strategy. Potential confounders will be identified using a directed acyclic graph and inverse probability of censoring weights will be applied to adjust for bias arising from artificial censoring. Subgroup analyses will be prespecified based on the potential sources of treatment-effect heterogeneity.

The institutional review board of West China Hospital, Sichuan University, approved this study (Approval No. 2025(1790)). Given the study's retrospective design and the use of de-identified data, informed consent was waived. The results of this research will be disseminated through publication in a peer-reviewed journal and presentation at scientific conferences.

ChiCTR2600121012.

To identify latent symptom subgroups, compare symptom network characteristics across subgroups and examine factors associated with subgroup membership among lung cancer survivors.

Cross-sectional study using latent profile analysis and symptom network analysis.

Four hospitals in Shanghai, China, including a national thoracic oncology centre, two tertiary general hospitals and one regional general hospital.

A total of 942 lung cancer survivors who had completed surgical treatment or received at least one course of initial antitumour therapy and were in a stable follow-up phase or treatment interval. The mean age was 64.43±10.70 years and 65.10% were male.

Primary outcomes were latent symptom subgroups identified by latent profile analysis and symptom network characteristics derived from partial correlation networks. Secondary outcomes were socio-demographic, clinical, functional and psychosocial factors associated with subgroup membership, assessed using multivariable multinomial logistic regression following least absolute shrinkage and selection operator (LASSO) variable selection.

Three symptom subgroups were identified: a low-symptom group (n=488, 51.80%), a moderate-symptom group (n=364, 38.64%) and a high-symptom group (n=90, 9.55%). Network density was descriptively higher in the high-symptom group than in the low-symptom group (0.468 vs 0.175). Central symptoms differed across subgroups, with cough in the low-symptom group, vomiting in the moderate-symptom group and distress in the high-symptom group. After LASSO selection and collinearity assessment, 22 predictors were entered into the final multivariable multinomial logistic regression model. Compared with the low-symptom group, surgery with adjuvant therapy was associated with higher odds of membership in the moderate-symptom group (adjusted OR (aOR)=4.054, 95% CI 2.094 to 7.850), whereas better exercise capacity was associated with lower odds of membership in the high-symptom group (6-minute walk distance ≥450 m: aOR=0.101, 95% CI 0.027 to 0.372). The final model had a Nagelkerke pseudo-R² of 0.522.

Symptom burden among lung cancer survivors is heterogeneous and differs in both severity profiles and network structure. Integrating latent profile analysis with symptom network analysis may provide a useful framework for stratified symptom assessment and individualised symptom management in survivorship care.

MR-31-24-027806 (https://www.medicalresearch.org.cn/clinicalResearch/researchInfo?id=eb897346-a67b-4465-a553-1d1a3488bc30).

The aim of this study was to establish a predictive model for opportunistic sarcopenia applicable to Chinese cancer patients, so as to quickly detect the occurrence of this condition and provide a basis for early clinical intervention.

A total of 522 malignant tumor patients admitted to the First Hospital of Hebei Medical University from October 2017 to March 2022 were retrospectively analyzed. Opportunistic sarcopenia was diagnosed by L3 SMI. Twelve variables were collected; risk factors were screened and modeled via univariate and multivariate regression in R Studio, and con-tinuous variable cutoff points were determined by SPSS. A nomogram was constructed and validated with clinical decision and calibration curves.

The prevalence of opportunistic sarcopenia in the study population was 66.1% (345/522). The final predictive model included six key variables: gender, body mass index (BMI), C-reactive protein (CRP) level, systemic immune-inflammation index (SII), prognostic nutritional index (PNI), and SII-PNI. The area under the curve (AUC) of the model was 0.890 (95% CI: 0.854-0.926), indicating high discriminative ability. The calibration curve showed good consistency between the model's predictions and the actual diagnostic results. Clinical net benefit analysis showed that when the threshold range was greater than 0.6, the clinical benefit rate of the predictive model was higher than those of relative appendicular skeletal muscle mass (RASM) and appendicular skeletal muscle mass index (ASMI).

The constructed nomogram model can accurately estimate the probability of opportunistic sarcopenia in cancer patients, facilitating its early screening and targeted prevention.

Cancer immunotherapy has substantially advanced cancer treatment, achieving durable responses in select malignancies. However, its widespread application is limited by significant challenges: low efficacy in many solid tumors, severe side effects, and immune evasion facilitated by the tumor microenvironment (TME). Nanotechnology offers a promising approach to address these obstacles. By employing nanoparticles (NPs), we can precisely deliver therapeutics to tumor sites, ensure controlled release to minimize side effects, and amplify the immune response, thereby substantially boosting the effectiveness of immunotherapy. This review comprehensively highlights the latest advancements in using nanotechnology to enhance cancer immunotherapy. This paper details various applications of nanotech in this field. It discusses smart nanoparticles that respond to TME signals to release drugs (e.g., checkpoint inhibitors) directly at the tumor, reducing systemic side effects and activating T-cells. We also explore how nanovaccines, which co-deliver tumor markers and immune boosters, can induce antigen-specific immune responses. Furthermore, mRNA-loaded nanoparticles can directly modify CAR T-cells inside the body, simplifying treatment and increasing efficacy. Strategies like using PLGA NPs to deliver immune enhancers such as IL-2 are also presented, which activate immune cells while minimizing systemic issues. The review also explains how nanoparticles can re-engineer the immunosuppressive TME to create an environment more conducive to immune action. We also emphasize that nanotechnology-enhanced adoptive therapies, particularly cytokine-induced killer (CIK) cell immunotherapy, hold great potential to improve tumor targeting, treatment persistence durability, and overall anticancer efficacy. Collectively, we highlight synergistic effects achieved by combining nanoparticles with other treatments like chemotherapy, radiation, photothermal/photodynamic therapy, and more, which can turn hard-to-treat tumors into susceptible targets. The integration of nanotechnology and immunotherapy holds the potential to meaningfully advance future cancer therapy.

Over 90% of children with cancer live in low- and middle-income countries (LMICs), where critically ill children are often managed by non-intensivists. We implemented a translational, hybrid workshop between Hospital General-Tijuana, Mexico, and Rady Children's Health-San Diego, USA, to enhance non-intensivists' knowledge and clinical skills in onco-critical care. Pre- and post-workshop assessments evaluated knowledge, self-reported confidence, and satisfaction in 17/20 participants. Knowledge increased by 13.0% (68.8% vs. 81.8%; p < 0.05). Confidence increased (5.9%-41.2% vs. 64.7%-94.1%; p < 0.05) in 6/8 topics: intracranial hypertension, superior vena cava syndrome, febrile neutropenia, septic/adrenal shock, and medullary compression. Satisfaction was high (88.2%). Our low-cost, context-adapted, and replicable workshop enhanced onco-critical care knowledge and confidence among non-intensivists caring for critically ill children with cancer, enabling transnational collaboration across the United States-Mexico border.

Melanotic neuroectodermal tumor of infancy (MNTI) is a rare neoplasm primarily affecting the craniofacial skeleton in infants. Management can be challenging in unresectable, multiply recurrent, or metastatic cases. Diagnosis requires local imaging assessment with magnetic resonance imaging (MRI) and computed tomography (CT) and histopathological confirmation. Surgery is the mainstay of treatment, achieving 80%-90% cure rates. Chemotherapy may be considered for advanced disease, whereas radiotherapy is generally avoided in young children. These recommendations were developed within European Cooperative Study Group for Pediatric Rare Tumors (EXPeRT) and European Reference Network Paediatric Cancer (ERN PaedCan) using a structured consensus process based on focused literature review and expert agreement. Multidisciplinary, risk-adapted management, and structured follow-up are essential.

In order to investigate the therapeutic mechanism of Jianpiyiqi Granule in juvenile myasthenia gravis (JMG) and find the immune-associated cytokines or signaling pathways targeted by this intervention.

(1) We extracted JMG serum samples from the sample bank of the Hebei Provincial Key Laboratory of Myasthenia Gravis before and after treatment. (2) Using Olink Immune Response Panel detects serum cytokines. Data were collated and analyzed using statistical software. Differentially expressed proteins (DEPs) were visualized using heat maps, volcano plots, and other tools. Differentially expressed cytokines were analyzed using KEGG enrichment pathway analysis to identify the relevant signaling pathways they participate in.

(1) Twelve of 92 cytokines were found to be differentially expressed from 20 patients before and after treatment, namely AXIN1, CCL11, CCL13, CCL20, CCL25, CCL3, CD40, IL12B, S100A12, SIRT2, SLAMF1, and STAMBP (|log₂FC| > 0.263; false discovery rate (FDR)-adjusted p  < 0.05). IL12B was upregulated while AXIN1, CCL11, CCL13, CCL20, CCL25, CCL3, CD40, S100A12, SIRT2, SLAMF1 and STAMBP were downregulated after treatment. Notably, three of these-CCL11, IL12B, and STAMBP-showed stronger statistical evidence, with FDR-adjusted p  < 0.01 and |log₂FC| > 0.263. (2) The following pathways were obtained by KEGG enrichment analysis of 12 cytokines: cytokine-cytokine receptor interaction, viral protein interaction with cytokine and cytokine receptor, chemokine signaling pathway, Toll-like receptor (TLR) signaling pathway, intestinal immune network for IgA production, IL-17 signaling pathway, NF-kappa B signaling pathway. (3) CCL11 and CCL20 were enriched in the IL-17 signaling pathway. We used enzyme-linked immunosorbent assay (ELISA) to retest additional serum samples before and after treatment from 12 JMG patients before and after treatment. The results showed a significant decrease in CCL11 and CCL20 in after-treatment serum (p  < 0.05).

Drug therapy for JMG revealed 12 differentially expressed cytokines. Due to the exploratory nature and sample volume constraints, only two candidate cytokines were validated by ELISA. We found that the cytokines CCL11 and CCL20-associated with the IL-17 signaling pathway-were downregulated after treatment. The drug therapy may inhibit MG progression by reducing the expression of IL-17-associated cytokines. At the same time, the drug reduced the expression of CCL3, CCL13, CCL25, and CD40, which may play a role in the abnormal proliferation of thymocytes and chronic inflammatory response at the neuromuscular junction. Future studies with multiplex assays are needed to confirm the involvement of other differentially expressed cytokines, such as SIRT2 and AXIN1, which may contribute to disease mechanisms outside the identified pathways.

Follicular lymphoma (FL) is the most common indolent non-Hodgkin lymphoma, characterized by a relapsing and remitting course and a median overall survival exceeding 15-20 years with modern therapy. While chemoimmunotherapy remains the cornerstone of frontline management, the rapid approval of novel agents, including bispecific antibodies, CAR T-cell products, and antibody-drug conjugates, has fundamentally reshaped the relapsed/refractory (R/R) landscape. This review summarizes current evidence across the treatment continuum and propose a practical, risk-adapted sequencing framework.

Bispecific antibodies (mosunetuzumab, epcoritamab) have demonstrated durable complete responses in heavily pretreated FL, with manageable toxicity profiles. CAR T-cell therapy (axicabtagene ciloleucel, lisocabtagene maraleucel, and tisagenlecleucel) are approved in R/R FL after two or more prior lines, offering high response rates albeit notable logistal and safety considerations. Frontline trials incorporating lenalidomide-rituximab have established chemotherapy-free option with long-term outcomes comparable to chemoimmunotherapy. Emerging data on antibody-drug conjugates and bispecific antibody combination therapy continue to expand the therapeutic arsenal. Despite favorable long-term outcomes for many patients with FL, relapse remains common and remission typically shortens with successive lines of therapy. The growing number of effective agents with distinct mechanisms of action creates both opportunity and complexity. Evidence-based sequencing strategies that account for prior therapy exposure, patient fitness and mechanism-specific considerations are increasingly critical to maximizing outcomes across the disease trajectory.