ABSTRACT Introduction Unequal access to care is associated with disparities in prevention, early detection, and outcomes of head and neck cancer (HNC), especially in underserved populations. Community‐engaged research (CEnR) aims to build capacity for community members to address health inequity via bidirectional partnerships with healthcare institutions. However, although HNC community screening events might increase HNC awareness, there is a paucity of HNC screening and prevention programs based on a community engagement framework. Methods and Analysis This pilot study utilizes mixed methodology in the development, implementation, and evaluation phases of a community engaged participatory research effort titled Community Head and Neck Cancer Knowledge, Engagement, Research and Screening (CHECKERS). The target community is a local faith‐based organization consisting primarily of an underserved immigrant population. An overseeing advisory board consisting of a transdisciplinary HNC team, community stakeholders, and community liaisons was assembled, and focus groups were held with community partners in the development phase to identify community resources/needs related to HNC prevention, risk factors, early detection, and health equity. Rapid analysis of the completed focus group sessions will inform the development of community education and screening events. Preliminary administration of the HNC knowledge and risk‐factor survey has begun and will continue during implementation. Quantitative and qualitative analysis of survey results, screening outcomes, and feedback from community stakeholders in the evaluation phase will be used to develop scalable, sustainable, and community‐driven interventions in the future. Ethics and Dissemination The described research study has been approved by the IRB of the parent institution. The results will be presented at relevant scientific meetings and disseminated through peer‐reviewed journals. Preliminary results will be used to develop interventions aimed at providing evidence of clinical benefits of mass screenings for preventing and detecting HNC, addressing the National Institutes of Health (NIH) NOT‐OD‐22‐179, Notice of Special Interest (NOSI): Addressing Evidence Gaps in Screening.
ABSTRACT Objective This single‐center retrospective cohort study evaluated whether, among patients with stage IV cancer who participated in a pragmatic “alkalization therapy”—defined as a low potential renal acid load diet plus oral sodium bicarbonate and/or potassium/sodium citrate—urinary pH was associated with long‐term survival. Methods All consecutive patients with stage IV cancer who first attended the Karasuma Wada Clinic between January 2014 and April 2024 were screened. Of 1414 patients with stage IV cancer, 1096 who had at least three clinic visits were included in the analytic cohort. All patients received alkalization therapy, consisting of low potential renal acid load (PRAL) dietary counseling, with oral sodium bicarbonate and/or potassium/sodium citrate added when the urinary pH target was not achieved with dietary intervention alone. Overall survival (OS) was estimated using the Kaplan–Meier method, and survival was compared between subgroups stratified by the 12.5% visit‐order‐trimmed mean urinary pH, defined as the mean after excluding the first and last 12.5% of measurements according to visit order. This study was conducted in accordance with the Declaration of Helsinki, approved by The University of Electro‐Communications (Approval number: H24052), and registered with the UMIN Clinical Trials Registry (UMIN000057017; date of registration: February 14, 2025). Results Across more than 20 cancer types, Kaplan–Meier analysis estimated a 5‐year overall survival of 39.8% and a 10‐year overall survival of 28.8%. When stratified by urinary pH (cutoff, 5.5), the pH ≤ 5.5 group ( n = 43) had a 1‐year survival rate of 31.2%. In contrast, the pH > 5.5 group ( n = 1053) had a 1‐year survival rate of 73.2%, with 5‐ and 10‐year survival rates of 38.5% and 29.2%, respectively. In the three‐group analysis, outcomes were most favorable in the pH ≥ 6.5 group (log‐rank p < 0.0001). In the Cox proportional hazards model stratified by primary tumor site and adjusted for age at the first clinic visit and sex, urinary pH was the only significant covariate; each 1‐unit increase in urinary pH was associated with a 25.3% lower hazard of death (HR, 0.747; 95% CI, 0.635–0.878; p = 0.0004). Conclusions In this retrospective stage IV cancer cohort, long‐term survival exhibited a long‐tail structure with an apparent late survival plateau in a subset of patients. Higher urinary pH may be an accessible measure influenced by renal acid excretion, diet, hydration, medication, and renal function. These findings should be interpreted as associative and hypothesis‐generating, rather than causal. Prospective studies with standardized treatment and longitudinal data capture are warranted to clarify the causality and clinical utility.
ABSTRACT Background Patients with stage I–III non‐small cell lung cancer (NSCLC) can have very different outcomes, even when they have the same anatomic stage. This suggests that tumor biology plays an important role in prognosis. Fraction genome altered (FGA) is a measure of chromosomal instability that can be calculated from routine targeted next‐generation sequencing (NGS) already used in clinical care. We evaluated whether FGA is associated with survival in early‐stage NSCLC and whether it adds information beyond standard clinical factors and tumor mutation burden (TMB). Methods We studied 7722 patients with NSCLC who underwent clinical‐grade targeted NGS with available copy‐number data. FGA was calculated from copy‐number profiles and analyzed by quartiles and as high (top quartile) versus low (lower three quartiles). Overall survival (OS) was evaluated using Kaplan–Meier analysis and Cox regression models adjusted for age, sex, smoking history, histology, disease stage, sequencing panel, and TMB. Results Higher FGA was associated with worse OS in stage I–III NSCLC. Five‐year OS declined from 65.6% in the lowest FGA quartile to 39.6% in the highest. Patients with high FGA had significantly poorer survival compared with those with low FGA ( p < 0.001). After adjustment for clinical factors, high FGA remained independently associated with mortality, whereas TMB did not. Conclusions Chromosomal instability measured by FGA is associated with survival in stage I–III NSCLC and provides useful prognostic information beyond standard clinical features and TMB. FGA may help identify early‐stage patients at higher risk who could benefit from closer follow‐up or clinical trials.
ABSTRACT Oral squamous cell carcinoma (OSCC) usually originates from the precancerous lesions of oral mucosa and accounts for approximately 90% of oral cancers. In‐depth understanding of pathogenesis, hallmarks, and etiological factors is a crucial prerequisite for advancing the diagnosis and treatment for OSCC patients. This review aims to present the latest evidence on the risk factors, diagnostic methods, and therapeutic strategies for OSCC. The major risk factors for OSCC include smoking, drinking, chewing areca nuts, and genetic mutations. In the diagnosis of OSCC, biopsy is recognized as the gold standard, whereas toluidine blue staining serves as the simplest non‐invasive and highly accurate auxiliary method. Various therapeutic interventions, such as chemotherapy, radiation therapy, immunotherapy, and nanomedicine, have been proposed for the prevention and treatment of OSCC. This review systematically synthesizes the current evidence, with the intention of providing valuable insights for the clinical and research communities and facilitating the progress of future research in this field.
ABSTRACT This study aimed to characterize the expression pattern of TACC1 in gastric cancer (GC), investigate its correlation with clinicopathological features and patient prognosis, and evaluate its potential as a prognostic and therapeutic biomarker. Differential expression and immune infiltration analyses of TACC1 were performed using the TIMER and GEO databases. The association between TACC1 expression and clinicopathological characteristics in GC was further examined using the UALCAN database. Based on expression data from TCGA and GEO GC cohorts, univariate and multivariate Cox regression analyses as well as survival analyses were conducted using R software to assess the prognostic value of TACC1. Finally, co‐expression analysis was performed via the LinkedOmics database, followed by functional enrichment analysis of TACC1 co‐expressed genes. Our bioinformatics results demonstrated that upregulated TACC1 expression is significantly associated with poor prognosis in patients with GC, supporting its potential as a novel prognostic biomarker for gastric cancer.
Lipid nanoparticles (LNPs) represent the most clinically advanced platform for RNA delivery and have enabled major breakthroughs in vaccines and gene therapies. However, their broader application is still limited by inefficient extrahepatic delivery, immunogenicity, and insufficient control over tissue‐ and cell‐specific targeting. This review provides a mechanistic overview of recent advances in LNP engineering for RNA therapeutics. We systematically analyze how key physicochemical parameters and structural elements, including ionizable lipid headgroups, linkers, tail architectures, helper lipids, cholesterol analogs, and surface modifications, govern biodistribution, endosomal escape, immunogenicity, and therapeutic efficacy. Emerging targeting paradigms, encompassing ligand‐mediated active targeting, formulation‐driven intrinsic targeting, and administration‐route optimization, are discussed with a focus on tumor and immune organ delivery. In addition, we highlight enabling methodologies such as DNA barcoding, multiplexed in vivo screening, and data‐driven lipid design that are reshaping LNP discovery. Finally, translational challenges and future directions for precision RNA delivery in cancer therapy are discussed, with an emphasis on how rational LNP design can be leveraged to overcome cancer‐specific barriers such as tumor heterogeneity, stromal constraints, and the immunosuppressive tumor microenvironment (TME).
Oral cancer is a significant public health concern, with disproportionately higher incidence and mortality in rural, regional, and remote Australia. General dental practitioners (GDPs), as frontline providers, are critical to early detection through routine screening. This pilot study aimed to assess the feasibility of surveying GDPs' knowledge, confidence, and perceptions of oral cancer screening, with a focus on rural–metropolitan differences to identify gaps and guide targeted interventions. A cross-sectional online pilot survey was distributed to GDPs across Australia (Ethics approval: HEC24419). The survey collected sociodemographic data, current oral cancer screening practices, knowledge of risk factors and pathology, self-assessed confidence in screening, and perceptions of screening practices. Data were analysed using descriptive statistics and non-parametric exploratory analyses. Of 20 respondents, 18 met the inclusion criteria. Most practitioners reported routine or risk-based screening, however, gaps were identified in patient education, recognition of less common oral potentially malignant disorders, and confidence, particularly for extra-oral examinations. Exploratory analyses did not detect statistically significant differences between rural and metropolitan practitioners ( p > 0.05). This pilot study demonstrates the feasibility of assessing Australian GDPs' preparedness for oral cancer screening using an online survey. Although findings are exploratory, they highlight important knowledge and confidence gaps with implications for undergraduate education and continuing professional development. The results provide essential groundwork for a future, adequately powered national study aimed at strengthening early detection capacity and reducing diagnostic delays. GDPs are often the first point of contact for patients and play a key role in early detection of oral cancer. Recognising oral potentially malignant disorders (OPMDs) during routine dental exams is essential to prevent malignant transformation. This study identifies gaps in practitioners' knowledge and confidence in identifying OPMDs, underscoring the need for targeted continuing education and training. Enhancing practitioner competence in early recognition can improve patient outcomes, facilitate timely referrals, and help reduce the burden of oral cancer in the community.
Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet a substantial proportion of patients develop primary or acquired resistance. Understanding the mechanisms underlying this resistance is critical for improving therapeutic outcomes. This review comprehensively examines resistance mechanisms to cancer immunotherapy through a host–tumor interaction perspective, integrating tumor-intrinsic factors, the immunosuppressive microenvironment, and systemic host characteristics. Resistance arises from multiple interconnected mechanisms: (1) tumor-intrinsic defects, including impaired antigen presentation, aberrant oncogenic signaling (MAPK, PI3K/AKT/mTOR, and WNT/β-catenin pathways), and metabolic reprogramming; (2) tumor-extrinsic factors, including immunosuppressive immune cells (MDSCs, Tregs, and M2 macrophages), physical barriers, and metabolic competition; and (3) systemic host factors, including gut microbiome composition and HLA polymorphisms. These mechanisms collectively create a formidable barrier to effective antitumor immunity. A comprehensive understanding of this multimodal crosstalk is essential for developing effective strategies to overcome resistance. Rational combination therapies targeting multiple nodes within the cancer-immunity cycle, informed by patient-specific resistance profiles, represent a promising approach to improve immunotherapy efficacy and expand the population of responders.
Large real-world breast cancer datasets with molecular profiling are increasingly used to estimate the benefit of adjuvant chemotherapy in hormone receptor-positive, HER2-negative (HR+/HER2−) disease and are often interpreted alongside randomized trial data. Since chemotherapy usage in routine practice is strongly influenced by baseline clinical risk and tumor biology, observed survival associations may reflect treatment selection rather than treatment effect. In this study, we analyzed the population-based RNA-sequencing dataset GSE96058, including 3409 primary breast cancers with long-term follow-up. Among 2536 patients with HR+/HER2− disease treated with adjuvant endocrine therapy, we evaluated overall survival by chemotherapy exposure within PAM50-defined Luminal A and Luminal B subtypes. In unadjusted analyses, chemotherapy was associated with improved overall survival, particularly in Luminal B tumors (hazard ratio (HR) 0.29 and 95% CI 0.16–0.53). After inverse probability of treatment weighting with trimming, this association remained large (HR 0.25 and 95% CI 0.12–0.55). However, after restricting analyses to patients with comparable likelihood of receiving chemotherapy and applying overlap-restricted doubly robust adjustment, chemotherapy was no longer significantly associated with overall survival in either subtype. In the overlap-restricted cohort ( n = 1194; 80 deaths), adjusted HRs were 1.06 (95% CI 0.49–2.28) for Luminal A and 0.60 (95% CI 0.26–1.39) for Luminal B disease. These findings highlight the limitations of real-world molecular cohorts for estimating chemotherapy benefit without careful attention to treatment selection.
The basic treatment principle for patients with advanced oral cancer is holistic therapy based on surgery. However, the radical resection may cause functional disorders in patients and there is also a risk of local recurrence and distant metastasis. Neoadjuvant immunochemotherapy can promote complete resection and improve treatment outcomes for patients with advanced oral cancer by reducing tumor burden and clearing microscopic metastases. Here, we describe the case of a 63‐year‐old female patient who presented in early 2025 with oral squamous cell carcinoma (OSCC) of the left buccal mucosa. The patient was treated with two cycles of neoadjuvant immunochemotherapy with the specific regimen of tislelizumab, cisplatin, and albumin‐bound paclitaxel, followed by surgical treatment after the neoadjuvant therapy. The patient's clinical response was assessed as partial response with good pathological response. This case presented the application of neoadjuvant immunochemotherapy in patients with locally advanced OSCC. In terms of short‐term efficacy, the neoadjuvant immunochemotherapy regimen comprising tislelizumab, cisplatin, and albumin‐bound paclitaxel helped patients achieve tumor shrinkage and improve surgical outcomes.
In this study, we evaluated the efficacy and safety of using an aortic balloon to control blood loss during lower lumbar tumor resection. We retrospectively reviewed 82 patients with tumors involving the lower lumbar spine (L4, L5, or Both), who were treated at our center from July 2015 to September 2023. We compared 25 patients who underwent lower lumbar tumor resection with aortic balloon occlusion, and 57 patients who underwent the same tumor resection procedure without no aortic balloon occlusion. The demographic, oncologic, and surgical characteristics of patients were compared between the two groups. Balloon‐related complications were assessed by reviewing the medical records. The demographics of the two groups, including tumor type, vascularity, and site; previous history of surgery or radiotherapy; preoperative embolization; surgical approach; resection type; and surgical margin for primary malignant tumors, did not differ significantly between the two groups. The group with aortic balloon insertion had significantly lower mean intraoperative blood loss (1580 ± 1071 mL, range 200–4700 mL vs. 2241 ± 1391 mL, range 300–7100 mL, respectively; P = 0.02), shorter surgical duration (200 ± 83 min, range 95–450 min vs. 247 ± 99 min, range 115–530 min, respectively; P = 0.048), and lower volume of packed red blood cells (pRBC) (654 ± 519 mL, range 120–2600 mL vs. 962 ± 708 mL, range 0–3200 mL, respectively; P = 0.039) than the group without aortic balloon insertion. Three patients experienced complications related to the use of the aortic balloon: two developed a local hematoma at the needle puncture site and one developed femoral artery thrombosis. Our findings revealed that aortic balloon occlusion decreased intraoperative blood loss, reduced pRBC transfusion, and shortened the surgical duration. In addition, balloon‐related complications were uncommon. This technique could be considered during resection of hypervascular lower lumbar tumors.
This work compares the effect of African walnut oil and docosahexaenoic acid (DHA) on cancer antigen C15‐3 (CA15‐3), biochemical, and histopathological markers of rats with 7,12‐dimethylbenz[a]anthracene‐induced (DMBA) breast cancer. 18 rats with tumor were randomized into three groups of six rats each: The negative control, the positive control, and test group that respectively received distilled water (250 mg/kg), DHA (125 mg/kg) and African walnut oil (1000 mg/kg) by gavaging every day for 28 days. The six rats that were not induced served as normal group. After sacrifice, blood was collected and centrifuged to obtain the serum on which the breast cancer antigen CA15‐3 level, the lipid profile, serum enzymes, and creatinine levels were measured. Organs were collected for histopathological studies. Results showed significantly higher HDL levels in groups taking DHA and African walnut oil. African walnut oil and DHA also significantly decreased the CA15‐3, Aspartate aminotransaminase, alanine aminotransaminase, lactate dehydrogenase, and creatinine levels of rats compared to the negative control group. They also exhibited a protective effect on organs against the DMBA. African walnut oil and DHA have protective effects and may help in the management of breast cancer if added to the diet.
Bone metastasis is highly prevalent in breast, prostate, and lung cancers and is strongly correlated with poor clinical outcomes and the occurrence of skeletal‐related events (SREs). Bidirectional communication between tumor cells and bone‐resident cells provides selective advantages that promote tumor growth, resulting in either bone destruction or the deposition of a new bone matrix. Current treatment strategies are predominantly palliative, underscoring the urgent need for the development of novel and more effective therapeutic targets. In this review, we summarize the key findings regarding the interactions and molecular mechanisms between cancer cells and major cellular components of the bone microenvironment, including osteoblasts, osteoclasts, endothelial cells, and immune cells. This crosstalk between metastatic cancer cells and the bone microenvironment not only promotes tumor cell survival and colonization in bone, but also modulates the activity of osteoblasts and osteoclasts and remodels the bone microenvironment. Notably, targeting these cell‐cell interactions offers promising therapeutic strategies for the prevention and treatment of bone metastasis.
The aquaporin‐9 (AQP9) has been implicated in tumorigenesis, but its pan‐cancer prognostic and immunology remain poorly understood. Therefore, we explored the role of AQP9 in pan‐cancer. We systematically analyzed the expression of AQP9 across human cancers using multi‐omics data from The Cancer Genome Atlas (TCGA), Genotype‐Tissue Expression (GTEx), Oncomine and Tumor Immune Estimation Resource (TIMER2) database. AQP9 was overexpressed in most tumors, while its expression was reduced in cholangiocarcinoma (CHOL), hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous carcinoma (LUSC) and prostate adenocarcinoma (PRAD). Survival analysis revealed that elevated AQP9 levels independently predicted poor prognosis in adrenocortical carcinoma (ACC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), lower‐grade glioma (LGG), and testicular germ cell tumors (TGCT). Importantly, AQP9 demonstrated significant correlations with tumor immune regulation, including associations with immune cell infiltration, cytokine activity, and immune checkpoint genes. Genomic alterations in AQP9 were linked to dysregulated immune pathways, and enrichment analysis highlighted its role in leukocyte migration and chemokine signaling. Furthermore, high AQP9 expression was associated with immunosuppressive tumor microenvironments, suggesting its potential to disrupt antitumor immunity. Our findings suggest that elevated AQP9 levels were associated with poor prognosis and provide new insights into the dual role of AQP9 in tumor progression and immune evasion.
Colorectal cancer (CRC), as the second most common cause of cancer death worldwide, has seen a significant increase in its incidence rate in recent years. However, the current major clinical treatment methods, such as surgery, chemotherapy and radiotherapy, still have certain limitations and are difficult to achieve a complete cure. In recent years, with the continuous integration of nanomaterials and the field of tumor treatment, porous organic frameworks (POFs) have gradually become a research hotspot due to their highly controllable structure and adjustable physicochemical properties, exhibiting significant advantages in cancer treatment. In this review, we comprehensively summarize the latest research progress of POF-based nanomaterials in traditional and novel treatment methods for colorectal cancer, elucidating its underlying treatment mechanisms, and discusses the challenges and directions of future research.
Anoikis represents a distinct type of programmed cell death that serves a critical function in tumor development and metastatic. Despite its significance, there remains a notable gap in comprehensive studies that explore the role of Anoikis specifically within the context of colon cancer (CC). Thus, it becomes imperative to pinpoint Anoikis‐related genes (ARGs) that could provide valuable prognostic insights into the progression and outcomes of colon cancer. Identifying these ARGs may ultimately enhance our understanding of the disease and contribute to improving patient management strategies. RNA sequencing data, along with clinical details from cancerous tissue samples, were sourced from the TCGA and GEO databases, in addition to the Genecards and Harmonizome platforms, to identify differentially expressed ARGs (DE‐ARGs). The ensuing analyses encompassed Gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein–protein interaction (PPI) examinations. To discover DE‐ARGs associated with prognosis, single‐factor Cox regression analysis was employed, alongside evaluations of single nucleotide variations (SNVs), copy number variations (CNVs), and methylation levels. Consensus clustering was applied to categorize patient subtypes and to investigate differences in survival outcomes, clinical characteristics, and immune cell infiltration (ICI) across these groups. A risk assessment model was constructed utilizing LASSO‐ Cox regression analysis. The model's viability in a clinical context was validated through survival curve analysis, receiver operating characteristic (ROC) curve assessment, and the generation of array plots. Additionally, the analysis explored variations in the ICI, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint (ICP) characteristics, and drug sensitivity of the model. Finally, immunohistochemistry (IHC) analysis confirmed the discrepancies in expression levels and prognostic implications between NATI and OGT. A total of 161 DE‐ARGs and 32 prognosis‐related DE‐ARGs were identified. Consensus clustering analysis divided CC patients into two unique subtypes. These subtypes showed differences in clinicopathological features, ICI, and prognostic outcomes. A prognostic risk model consisting of five ARGs (TIMP1, NAT1, EDAR, HOTAIR, and OGT) was constructed. Significant variations were observed in ICI, TMB, drug sensitivity, MSI, and expression of ICP‐related genes. Drawing from the findings of both single‐factor and multi‐factor prognostic assessments, a nomogram was developed that incorporates risk score, age, and stage classification. This nomogram's clinical effectiveness was validated by using calibration curve, cumulative hazard curve, and decision curve analysis (DCA). IHC findings supported the distinct expression levels of NAT1 and OGT in CC tissues as well as in adjacent tissues. A low level of NAT1 paired with a high level of OGT suggested a negative prognosis for the patients. According to the analysis of ARGs, CC can be divided into two categories. A prognostic risk model related to Anoikis for patients with CC was developed, highlighting its potential effectiveness in forecasting patient outcomes, understanding immune microenvironment changes, and evaluating chemotherapy responses. This work thus establishes a crucial theoretical basis for upcoming personalized precision therapies.
Neuroblastoma, the most common extracranial solid tumor in childhood, continues to challenge clinicians and researchers because of its heterogeneous nature and complex pathophysiology. Recent breakthroughs in molecular profiling revealed intricate genetic alterations driving tumor progression, necessitating an updated perspective on the disease’s pathophysiology. Rapid advancements in diagnostic techniques, including novel imaging modalities and molecular assays, warrant a thorough examination to guide clinical decision-making. Furthermore, the emergence of targeted therapies and immunotherapeutic approaches dramatically shifted the treatment landscape, creating an urgent need for a critical evaluation of their efficacy and integration into existing protocols. This comprehensive review is critically needed to synthesize the latest advancements in understanding the hallmarks of neuroblastoma, evolving diagnostic and therapeutic approaches. By consolidating current knowledge and identifying knowledge gaps, this review aims to provide a valuable resource for clinicians and researchers, potentially catalyzing new research directions and improving patient outcomes.
Cancer remains a formidable global health challenge. Owing to the unsatisfactory curative effects and severe side effects, it is urgent to explore safer and more effective therapeutic alternatives and drugs. Chlorogenic acid (CGA), a natural polyphenol, has emerged as a promising candidate for cancer therapy due to its multiple functions and minimal toxicity. Preclinical and clinical studies have demonstrated that CGA exerts potent anticancer effects through immunomodulation, induction of programmed cell death (PCD), cell cycle regulation, inhibition of tumor invasion and metastasis, suppression of angiogenesis, modulation of oxidative stress, and enhancement of chemotherapy efficacy. These diverse mechanisms enable CGA to target multiple hallmarks of cancer simultaneously, addressing the complexity and heterogeneity of tumor biology. This review comprehensively summarizes the latest research progress on CGA in cancer therapy, elucidates its underlying molecular mechanisms, and discusses the challenges and directions of future research.
Nanozymes, by mimicking the catalytic sites of natural enzymes, have emerged as effective substitutes for traditional natural enzymes. However, the relationship between the physicochemical properties and activity of nanozymes is complex and nonlinear. Traditional laboratory screening and theoretical calculations struggle to handle large-scale samples and multidimensional parameters, resulting in inefficiency and high costs in the pursuit of high performance nanozymes. Efficiently screening and designing nanozymes with desirable properties remain a significant challenge. Machine learning (ML) technology can capture the complex nonlinear relationship between the physicochemical properties and activity of nanozymes, allowing for the simultaneous processing of multidimensional input variables, thereby achieving more accurate and efficient performance prediction. This study adopts a data-driven approach to propose an ensemble enzymatic activity prediction model, utilizing ML algorithms to understand the particle–activity relationship, thereby enabling the efficient screening of nanozymes with high peroxidase (POD)-like activity. The ensemble model integrates five sub-models, significantly improving prediction accuracy and enhancing generalization compared to single models, achieving an accuracy of 82.4%. External experimental validation results indicate that the model's activity screening outcomes for four nanozymes outside the dataset are consistent with the results of enzymatic activity assays. Further in vitro and in vivo experiments substantiate the effectiveness of the model-selected nanozymes with POD activity in tumor treatment. This study offers a promising strategy for screening antitumor nanozymes with the desired POD activity and demonstrates the potential of ML in the field of materials science.
Gastric cancer (GC) stands out as one of the most prevalent forms of malignant tumors globally, characterized by a notably high mortality rate. In spite of progress in medical science and treatment alternatives, the survival rate over 5 years continues to stay under 40%. In the realm of cancer biology, ferroptosis and cuproptosis represent two distinctive forms of programmed cell death that are gaining attention for their roles in tumor progression and treatment response. Ferroptosis is characterized by its dependence on lipid peroxidation and the resultant accumulation of reactive oxygen species (ROS) which ultimately induce cellular demise. On the other hand, cuproptosis operates through a different pathway, characterized by the direct interaction of copper ions with the acylating elements of the tricarboxylic acid cycle which ultimately leads to cell death. Ferroptosis and cuproptosis, that are types of programmed cell death associated with metals, play a significant role in the onset and progression of GC. This study intends to employ bioinformatics techniques to pinpoint genes that are differentially expressed genes (DEGs) linked to ferroptosis and cuproptosis that are significant for the prognosis of GC. Additionally, the study aims to develop a prognostic risk score model that will facilitate the prediction of patient outcomes based on these identified genetic factors. Transcriptome and clinical data from tissues of 412 patients with gastric adenocarcinoma and 36 adjacent non‐cancerous tissues were obtained from The Cancer Genome Atlas stomach adenocarcinoma collection (TCGA‐STAD) database. This analysis aimed to identify differentially DEGs associated with ferroptosis and cuproptosis that are linked to the prognosis of GC patients. Furthermore, gene expression data along with clinical details from 433 GC patients in the gene expression omnibus (GEO) database were combined to create a prognostic risk score model. Further investigations were carried out, encompassing pathway enrichment analysis, assessment of tumor mutation burden (TMB), evaluation of tumor immune dysfunction and exclusion (TIDE), single‐sample gene set enrichment analysis (ssGSEA), and analysis of the tumor microenvironment (TME). Validation was achieved through immunohistochemical examination of relevant gene expression in samples collected from GC patients. Twelve DEGs linked to the prognosis of GC were discovered, leading to the creation of a prognostic risk score model that incorporates four genes involved in ferroptosis (NOX4, GLS2, MYB, NNMT) alongside one gene related to cuproptosis (GCSH). Analysis of pathway enrichment revealed a notable accumulation of the DEGs within several signaling pathways associated with the extracellular matrix. In addition, examinations of immune cell infiltration demonstrated significant variations in TMB, the quantity of immune cells present within the tumor, their functional roles, and the TME when contrasting high‐risk and low‐risk groups. Findings from immunohistochemical studies showed that GCSH and GLS2 show varying levels of expression in gastric cancer tissues and have a correlation with patient prognosis. A prognostic risk model specifically designed for gastric cancer was developed, comprising five distinct genes. This model demonstrates a strong ability to accurately forecast both the prognosis of gastric cancer patients and the effectiveness of immunotherapy treatments they may undergo.
