Since nuclear factor of κ‐light chain of enhancer‐activated B cells (NF‐κB) was discovered in 1986, extraordinary efforts have been made to understand the function and regulating mechanism of NF‐κB for 35 years, which lead to significant progress. Meanwhile, the molecular mechanisms regulating NF‐κB activation have also been illuminated, the cascades of signaling events leading to NF‐κB activity and key components of the NF‐κB pathway are also identified. It has been suggested NF‐κB plays an important role in human diseases, especially inflammation‐related diseases. These studies make the NF‐κB an attractive target for disease treatment. This review aims to summarize the knowledge of the family members of NF‐κB, as well as the basic mechanisms of NF‐κB signaling pathway activation. We will also review the effects of dysregulated NF‐κB on inflammation, tumorigenesis, and tumor microenvironment. The progression of the translational study and drug development targeting NF‐κB for inflammatory diseases and cancer treatment and the potential obstacles will be discussed. Further investigations on the precise functions of NF‐κB in the physiological and pathological settings and underlying mechanisms are in the urgent need to develop drugs targeting NF‐κB for inflammatory diseases and cancer treatment, with minimal side effects.

Lung cancer still contributes to nearly one‐quarter cancer‐related deaths in the past decades, despite the rapid development of targeted therapy and immunotherapy in non‐small cell lung cancer (NSCLC). The development and availability of comprehensive genomic profiling make the classification of NSCLC more precise and personalized. Most treatment decisions of advanced‐stage NSCLC have been made based on the genetic features and PD‐L1 expression of patients. For the past 2 years, more than 10 therapeutic strategies have been approved as first‐line treatment for certain subgroups of NSCLC. However, some major challenges remain, including drug resistance and low rate of overall survival. Therefore, we discuss and review the therapeutic strategies of NSCLC, and focus on the development of targeted therapy and immunotherapy in advanced‐stage NSCLC. Based on the latest guidelines, we provide an updated summary on the standard treatment for NSCLC. At last, we discussed several potential therapies for NSCLC. The development of new drugs and combination therapies both provide promising therapeutic effects on NSCLC.

Objectives. Primary mediastinal seminoma (PMS) was an uncommon carcinoma, and the appropriate treatment remained controversial due to the low incidence. We aimed to investigate the demographics and tumor biological characteristics to determine the potential effective treatment and predict the prognosis. Methods. Patients diagnosed with PMS were selected between 1975 and 2016 from Surveillance, Epidemiology, and End Results (SEER) database. Kaplan–Meier analysis and Cox proportional hazard model were conducted to determine the prognostic factors, and nomograms were employed to visually predict the prognosis. Concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) curve were conducted to validate the prediction model. Results. A total of 476 patients were included with a median age of 31 years (range, 2–76 years), and a median size of the tumor was 11.6 cm (range, 0.2–24.0 cm). The 5- and 10-year overall survival (OS) rates were 70.4% and 68.4%, respectively. Age, the extent of the primary site, metastatic status, and surgery performance were independent prognostic factors. Not received surgery was considered a poor prognostic factor for OS (HR, 1.86; 95% CI, 1.13–3.03; ). The C-index was 0.733 (95% CI, 0.685–0.781) and 0.819 (95% CI, 0.737–0.901) for internal and external validation for predicting OS, respectively. The area under the ROC curve (AUC) was 0.743 (95% CI, 0.681–0.804) for predicting OS (sensitivity, 0.532; specificity, 0.887) in the training cohort. Conclusions. The nomogram could efficiently predict the survival of patients with PMS. Surgery was the potential effective treatment, and chemotherapy was strongly recommended for patients over 40 years.

First, the study by Wang et al. investigates the rare clinical co-occurrence of medullary and papillary thyroid carcinoma. Their comparative analysis indicates that patients with both tumor types exhibit disease invasiveness and prognosis similar to those with medullary thyroid carcinoma alone. This finding suggests potentially independent oncogenic drivers. However, it also raises a profound question: Could a permissive local niche, shaped by common endocrine or immune factors, provide the foundation for the development of both tumors within the same gland? This question connects the case study to broader theories of the tumor microenvironment.The review by Wang et al. systematically elaborates on the multifaceted functions of adipose-derived mesenchymal stem cells (ADSCs), positioning them as central metabolic and immunomodulatory integrators within the tumor microenvironment. This review clarifies that ADSCs can translate systemic endocrine and metabolic signals into highly context-dependent pro-or anti-tumor effects. This work highlights the plasticity of stromal cells as a critical bridge connecting systemic metabolic disorders to local tumor progression, clearly exemplifying the central role of the immunometabolic axis in cancer advancement.The work by Xu et al. employs a bioinformatics approach to establish the prognostic significance of bile acid metabolism (BAM) in hepatocellular carcinoma (HCC), identifying NPC1 as a key biomarker and oncogenic driver. This study directly links this core hepatic metabolic pathway to tumor aggressive behavior, providing not only correlative evidence but also proposing a potential metabolic axis for risk stratification and intervention.The pharmacovigilance assessment by Brown et al. rigorously analyzes lymphoma risk in patients with lipodystrophy, a severe metabolic disorder involving leptin deficiency. By reporting cases in both drug-treated and treatment-naïve patients, this analysis crucially indicates that the inherent metabolic and immune dysregulation of the disease itself constitutes a significant carcinogenic risk factor. This distinction is fundamental for the precise risk-benefit assessment of therapeutic strategies in rare diseases.The detailed case report by Zhao et al. describes a case of severe thyroiditis induced by sintilimab. This report vividly embodies the direct clinical collision between oncology and endocrinology, where potent anti-cancer immunotherapy can trigger severe autoimmune-like endocrine toxicity. It underscores the shared immunological basis for both tumor eradication and endocrine tissue damage, emphasizing the necessity of adhering to relevant clinical guidelines for vigilant monitoring and early management.Finally, the study by Shen et al. explores the role of fatty acid metabolism (FAM) in papillary thyroid cancer (PTC), constructing a prognostic signature centered on SCD. Their work demonstrates that intrinsic metabolic reprogramming in tumor cells not only directly drives proliferation and invasion but also shapes an immunosuppressive microenvironment. This links metabolic dysregulation to both the tumor biology of PTC and its mechanisms of immune evasion.In summary, the research in this Topic presents a multidimensional understanding of the endocrine-immune-cancer axis. Several common themes emerge: the prognostic and therapeutic relevance of specific metabolic pathways; the dual nature of immune modulation in controlling cancer versus inducing endocrine pathology; and the critical importance of distinguishing disease-inherent risk from treatment-associated effects in clinical evaluation. Furthermore, the diversity of contexts involved-from common thyroid and liver cancers to rare lipodystrophy and immunotherapy toxicity-demonstrates the broad relevance of these interactive mechanisms, advocating for an integrated research paradigm that transcends traditional disciplinary boundaries [7][8][9] .These findings collectively point to several key directions for future research: First, targeting metabolic nodes such as SCD or NPC1 to disrupt tumor growth and remodel the immune microenvironment. Second, developing predictive biomarkers that combine metabolic and immune features for cancer risk stratification in populations with autoimmune/endocrine disorders and for predicting immunotherapy toxicity. Third, designing mechanism-based combination strategies, such as integrating metabolic modulators with immunotherapy. Fourth, implementing personalized monitoring and management plans for patients at this complex intersection.In conclusion, the contributions to this Research Topic mark significant progress in deciphering the intricate links between endocrine health, immune function, and cancer metabolism. By integrating clinical insights with molecular mechanisms, they collectively advance the framework for more precise prevention, prognostication, and treatment strategies for autoimmune-related and endocrine-influenced cancers.

Background: Portal vein tumor thrombus (PVTT) marks advanced hepatocellular carcinoma (HCC) and carries a dismal prognosis. Survival varies widely even within this stage, yet simple tools for individualized risk stratification remain scarce. Methods: We retrospectively enrolled 134 HCC patients with PVTT and randomly divided them into a training set (n = 94) and a validation set (n = 40). Clinical predictors were selected by variance inflation factor screening and backward elimination Cox regression. A radiomics score (Rad-score) was constructed from portal-venous phase computed tomography (CT) images using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression with 10-fold cross-validation. Three Cox models were built: a clinical model, an imaging model based solely on the Rad-score, and a combined model integrating both. Discrimination was assessed by C-index and time-dependent area under the curve (AUC). Calibration was examined with bootstrap-based calibration curves. Decision curve analysis evaluated net benefit. A nomogram was developed from the combined model. Results: Four clinical variables (alpha-fetoprotein (AFP), body mass index (BMI), high-density lipoprotein cholesterol (HDL-C), and alkaline phosphatase (ALP)) and two CT texture features (GLRLM_SRHGE and GLZLM_SZHGE) were retained as independent predictors. The combined model gave the highest C-index in both the training set (0.843) and the internal validation set (0.815). Its 1-year AUC reached 0.953 and 0.947 in the two sets. Calibration slopes ranged from 1.044 to 1.291 across time points, indicating a tendency toward mild overdispersion; nevertheless, decision curve analysis confirmed net benefit across clinically relevant thresholds. The combined model offered greater net benefit than either single-domain model across a 0–50% threshold range. A nomogram incorporating all five predictors was generated for individualized 12- and 24-month survival prediction. Conclusions: A combined model integrating routine laboratory variables and a CT-based radiomics score improved survival prediction over clinical or imaging models alone. The corresponding nomogram uses inputs from a basic blood panel and a single portal-venous phase CT, suggesting its potential as a low-cost prognostic stratification tool for HCC patients with PVTT, although external validation in prospective multicenter cohorts is required before clinical implementation.