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Accurate assessment of protein translation is crucial for understanding disease variant functions, but mRNA-protein discrepancy limits transcriptomics-based clinical oncology. While ribosome profiling directly measures translation, its clinical application is constrained by cost and complexity. Deep learning models like Translatomer infer translation efficiency from RNA-seq, but whether in silico translatomes provide superior clinical utility over standard RNA-seq remains unexplored. Here, we present a multidimensional framework evaluating the translational inference strategy across 15 independent datasets. Inferred translational profiles outperform conventional RNA-seq proxies in recapitulating ribosome occupancy and uncover the "dark proteome" through lncRNA translational potential prediction. We integrate this strategy into a translation-aware neoantigen pipeline, identifying high-confidence noncanonical neoantigens neglected by expression-based filtering. Applying this framework to glioma stratification reveals distinct subtypes and corrects high-risk patient misclassification by expression-based methods, as validated by survival analysis. Our study establishes translational inference as a cost-effective enhancement for precision oncology, refining patient stratification and expanding immunotherapeutic targets.
IntroductionThe 3-degree-of-freedom (3DOF) and 6-degree-of-freedom (6DOF) couches can enhance the accuracy of tumor localization in radiotherapy. However, the relationship between rotational and translational error corrections remains unclear. This study aims to evaluate the setup errors of three common tumor types using cone-beam computed tomography (CBCT) and registration analysis, with a focus on elucidating the coupling between rotational and translational errors, to optimize setup correction strategies and provide data support for the clinical application of 3DOF correction.MethodsA total of 46 patients with nasopharyngeal carcinoma (NPC), 48 with esophageal cancer(EC) and 23 with rectal cancer (RC) were enrolled in this cross-sectional study. For each patient, the pre-treatment CBCT images and planning CT images were registered offline using the same region of interest (ROI) and bony registration algorithm. Registration was performed in 3DoF and 6DoF modes, amounting to 1,720 registrations in total. The setup errors of registrations were analysed to investigate the relationship between rotational and translational deviations.ResultsSignificant registration errors were found only in the vertical direction for NPC and EC patients (P < 0.05), but not for RC patients (P > 0.05). The linear vector directions (D3D for 3DoF and D6D for 6DoF) showed strong linear correlations to varying degrees, R2NPC = 0.597, R2EC = 0.798, R2RC = 0.781 (P<0.01). Strong coupling correlations were observed between rotational and translational errors, particularly at the NPC site (pitch vs. ΔVrt: r = - 0.893; yaw vs. ΔLat: r = 0.826), the EC site (pitch vs. ΔLng: r = 0.544) and the RC site (pitch vs. ΔVrt: r = - 0.579).ConclusionA site-specific coupling exists between rotational and translational errors. When rotational errors exceed threshold ranges, performing site-specific rotational adjustments followed by translation is requisite. This strategy significantly enhances radiotherapy precision and patient safety in non-6DoF environments.
Children with pediatric brain tumors (PBT) follow a unique clinical course as diverse morbidities may emerge during treatment and may even persist into survivorship. Effectively addressing their needs requires joined efforts from various providers in order to provide optimal support. To investigate the challenges and needs of providers working in pediatric oncology with PBT patients and survivors. Providers with experience working with PBT patients were recruited throughout France to participate in a semi-structured interview. Data were analyzed following a reflexive thematic analysis method. 48 providers were interviewed, with a total of 46 participants included in the final study. Main challenges and needs were identified through 6 themes addressing the strained care environment, the triangular relationship with patients and their family, the complex needs of PBT patients, the emotional burden of care, the long journey of the care pathway, and coordination aspects. Main challenges encompassed poor communication among care teams, as well as patient-provider communication. Repeatedly facing poor prognoses and end-of-life situations were also identified as emotional challenges by providers. Participants also mentioned the necessity to decrease administrative task load, to increase the development of multidisciplinary care, and that training regarding specific PBT care needs is essential for providing optimal care. Pediatric neuro-oncology represents a unique and emotionally demanding field. Despite persistent communication and coordination challenges, findings highlight the critical importance of dedicated, well-coordinated multidisciplinary teams and long-term follow-up care to meet the complex needs of PBT patients and their families.
Molecular engineering, chemical biology, and translational oncology have transformed the landscape of targeted cancer therapies. Antibody-drug conjugates (ADCs) have advanced into clinically validated platforms that combine antigen-specific recognition with potent cytotoxic payloads, supported by innovations in linker chemistry, drug-to-antibody ratio (DAR) optimization, and bispecific or multispecific antigen targeting. Parallel to ADC development, targeted protein degradation (TPD) technologies-proteolysis-targeting chimeras (PROTACs), molecular glues, and emerging lysosomal and autophagy-based degraders enable the catalytic elimination of oncogenic drivers that were previously considered undruggable. Nanomedicine-based delivery enhances therapeutic selectivity, improves pharmacokinetics, and overcomes barriers to intracellular drug transport. Rational combination therapies that integrate these platforms with immune checkpoint inhibitors, kinase inhibitors, and tumor microenvironment (TME)-modulating agents address tumor heterogeneity and adaptive resistance more effectively than monotherapies. This review synthesizes the foundations of ADCs, multispecific antibodies, protein degraders, nanomedicine platforms, targeted small-molecule inhibitors, and their combination strategies. Clinically, the convergence of these modalities promises to extend durable responses to patient populations with refractory, molecularly complex malignancies by enabling individualized, mechanism-driven therapeutic selection. [Figure: see text].
Functional precision oncology (FPO) enables individualized therapy selection using patient-derived tumor models, yet the concordance of distinct ex vivo testing strategies remains unclear. Here, we compare two orthogonal drug sensitivity platforms across molecularly characterized models spanning diverse pediatric (n = 13) and adult (n = 6) cancers. A rapid ATP-based assay quantifies viability within three days, whereas a long-term dynamic image-based platform captures microtumor dynamics over two weeks, incorporating pharmacokinetic features. Up to 50 drugs were profiled across both platforms, with additional combinations evaluated in the long-term assay; genomics-guided targeted drugs served as benchmarks. Both approaches robustly distinguished responders from non-responders and showed strong agreement in therapeutic prioritization (96.5% within 95% limits of agreement). The long-term dynamic platform achieved 81% sensitivity and 78% specificity, while resolving response depth and distinguishing cytostatic from cytotoxic effects. A representative sarcoma case highlights clinical relevance: long-term dynamic profiling predicted disease progression, whereas the short-term assay captured early treatment-associated viability effects. These findings establish cross-platform reproducibility in FPO and provide a systematic benchmarking of such approaches. Defining their complementary utility will be essential for integrating FPO strategies into clinical decision-making.
Hematologic malignancies remain among the most challenging cancers to treat due to genetic heterogeneity, clonal evolution, and therapy resistance. Extracellular vesicles (EVs), particularly small EV (sEV)-enriched populations, have emerged as active mediators of disease biology, contributing to tumor progression, immune evasion, and chemoresistance through intercellular transfer of bioactive cargo. Recent advances in EV engineering have repositioned these vesicles as programmable delivery platforms capable of transporting nucleic acids, proteins, and chemotherapeutic agents with improved targeting potential. Preclinical studies across multiple hematologic models demonstrate that engineered EVs can induce immune activation, modulate oncogenic signaling pathways, and partially overcome drug resistance. However, these findings remain largely confined to experimental settings, with limited standardization of loading efficiency, biodistribution, and functional potency. Clinically, EV-based applications in hematology are still at an early stage, with most studies focused on biomarker discovery and supportive therapies rather than direct antitumor interventions. In parallel, theranostic EV platforms and liquid biopsy approaches offer promising opportunities for minimally invasive disease monitoring, although their clinical validation remains incomplete. Artificial intelligence (AI) further enhances this field by enabling advanced biomarker analysis and guiding cargo design and targeting strategies, yet its therapeutic applications are still largely exploratory. Despite key challenges, including vesicle heterogeneity, donor variability, suboptimal cargo loading, and manufacturing constraints, these limitations are primarily technical and may be addressed through standardization and engineering optimization. Collectively, EV-based systems represent a promising but still maturing platform with the potential to contribute to next-generation precision oncology in hematologic malignancies.
This cross-sectional study was designed to assess the informed consent quality in cancer clinical trials in China. We further examined the consistency between cancer patients' objective knowledge and subjective understanding of the trial, as well as patient-related factors that influence the quality of informed consent. This cross-sectional research was conducted at a tertiary cancer hospital in Beijing, China, between April 2023 and March 2024. To assess objective knowledge and subjective understanding of the consent provision and clinical trial, all participants completed a form comprising demographic items and the Quality of Informed Consent Questionnaire. Data were analyzed using correlation analyses, descriptive statistics, and quantile regression. For 304 cancer patients, the median objective knowledge as well as subjective understanding scores were 69.20 (IQR, 60.08-76.90) and 61.60 (IQR, 37.50-82.10), respectively. The correlation coefficients of the total score and each dimension between objective knowledge and subjective understanding ranged from 0.113 to 0.633, p < 0.050. Quantile regression analysis showed that age, level of education, marital status, primary caregiver, previous participation in clinical trials, and anti-tumor treatment experience significantly influenced both objective knowledge and subjective understanding. Cancer patients who participated in clinical studies showed moderate informed consent quality. Objective knowledge and subjective understanding of the trial content were significantly positively correlated. The correlations in the "Alternatives" dimension were weak and warrant improvement. The informed consent quality with different patient characteristics was heterogeneous, and the influence of these characteristics varied across quantiles.
Chemotherapy-induced cardiotoxicity is a significant difficulty in chemotherapy, contributing to long-term morbidity and reduced quality of life among cancer survivors. The NLRP3 inflammasome is a crucial molecular association between chemotherapeutic stress and inflammatory cardiomyocyte death, despite the fact that oxidative stress, mitochondrial dysfunction, calcium imbalance, and endothelial injury are well-known factors. NLRP3 activation increases myocardial inflammation and structural damage by stimulating Gasdermin D-dependent pyroptosis and caspase-1-mediated upregulation of IL-1β and IL-18. Another important upstream process that promotes NLRP3 activation during chemotherapy exposure is mitochondrial ROS-induced dissociation of TXNIP. Anthracyclines, antimetabolites, alkylating agents, platinum compounds, and microtubule inhibitors are just a few of the chemotherapeutic classes in which NLRP3 is involved. This review integrates current knowledge of NLRP3 structure, priming and activation pathways, and downstream signalling. This broader perspective illustrates the wider impact of inflammasome-mediated pathophysiology in chemotherapy-induced cardiac failure and goes beyond traditional doxorubicin-centered treatments. The review also provides an overview of the therapeutic landscape of selective NLRP3 inhibition, including natural modulators such as oridonin, curcumin, resveratrol, honokiol, and flavonoids, as well as synthetic inhibitors such as MCC950, CY-09, OLT1177 (dapansutrile), and tranilast. Synthetic molecules exhibit strong target specificity by suppressing NACHT ATPase activity, preventing ASC oligomerization, or inhibiting NEK7-dependent assembly, whereas natural compounds provide broader antioxidant and anti-inflammatory actions with favourable safety. Emerging evidence suggests synergistic benefits when NLRP3 inhibition is paired with antioxidants or established cardioprotective agents. Despite encouraging preclinical findings, translational challenges remain, including long-term safety assessment. Modulation of NLRP3 inflammasome activation has emerged as a potential intervention to limit chemotherapy-induced cardiac injury and dysfunction in cardio-oncology.
Radiotherapy is a major component of cancer treatment and contributing to the cure of approximately 220,000 patients annually in France, and to sustained long-term disease control in a substantial proportion of patients. Continuous technological advances - including image-guided radiotherapy, adaptive radiotherapy, and emerging ultra-high dose rate techniques - are transforming clinical practice and improving therapeutic outcomes. However, these innovations also raise important challenges related to equitable access, sustainable financing, workforce capacity, professional training, and the maintenance of high standards of quality and safety. The Société française de radiothérapie oncologique (SFRO; the French society of radiation oncology) conducted a national strategic reflection on the future of radiotherapy in France. Through multidisciplinary consultation involving radiation oncologists, medical physicists, radiation therapists, and healthcare stakeholders, a white paper was developed to assess current challenges and define priorities for the coming years. Four strategic priorities emerged: (i) ensuring equitable access to modern radiotherapy technologies across the national territory; (ii) strengthening patient-centred care and supportive care throughout the treatment pathway; (iii) reinforcing safety and quality frameworks in an increasingly complex technological environment; and (iv) improving workforce planning, training, translational and clinical research, and professional recognition within the radiotherapy field. Ten proposals are outlined to support innovation, strengthen research capacity, modernize financing mechanisms, enhance patient engagement, and address workforce shortages, particularly among radiation therapists and dosimetrists. The recommendations presented in this white paper aim to guide policymakers and healthcare stakeholders in sustaining the development and international competitiveness of radiation oncology in France.
Cancer remains a major global health burden, and the disconnect between preclinical models and clinical outcomes continues to hinder progress in oncology. Conventional two-dimensional (2D) cell cultures fail to recapitulate the in vivo tumor microenvironment (TME) and consequently show poor predictive power for drug responses. Animal models provide systemic insights but are constrained by interspecies differences, limited throughput, and high costs. Advanced three-dimensional (3D) in vitro platforms, such as spheroids, organoids, and organ-on-chip systems, have improved physiological relevance; however, they often lack the spatial control, reproducibility, and integrative capacity needed to capture the full complexity of the TME. This review posits that the unique value of 3D bioprinting in cancer research lies in its ability to reproducibly integrate the multicomponent complexity of the TME within a controllable spatial framework, a capability that no existing 3D model can provide simultaneously. We outline the technical foundation for TME reconstruction by 3D bioprinting, which encompasses bioink design, printing strategies, and the construction of complex tumor models. We subsequently summarize its applications in tumor biology, drug screening, personalized therapy and preclinical evaluation, and discuss translational challenges, interdisciplinary integration and future research directions. This review is intended to advance both basic cancer research and precision oncology.
Lung cancer is one of the malignant tumors with the highest incidence and mortality rates. Most patients are diagnosed at advanced stages, thus missing the golden period for diagnosis and treatment. Tissue biopsy is the most commonly used method for diagnosing lung cancer, but it is an invasive procedure. Patients with poor physical conditions may be unable to tolerate it, and it may even cause complications such as infection, pneumothorax and hemorrhage. On the other hand, repeated sampling is difficult to perform, which makes dynamic monitoring of tumor changes impossible, thus posing a significant obstacle to the adjustment of subsequent treatment plans. Emerging molecular diagnostic technologies, represented by liquid biopsy, have been developed rapidly. This may become one of the promising approaches for non-invasive monitoring of lung cancer. This review aims to summarize the biological basis, clinical applications, limitations, and future perspectives of ctDNA-based liquid biopsy in lung cancer. Relevant literature was identified through PubMed and a series of major oncology journals. Articles published in English within the past decade were preferentially considered. The selection focused on studies related to circulating tumor DNA (ctDNA)-based liquid biopsy in lung cancer, including its biological basis, clinical applications, and translational potential.Keys Content and Findings: This review describes in detail liquid biopsy centered on ctDNA, summarizes its application advantages in the diagnosis and treatment of lung cancer, and systematically analyzes its clinical translation value. This technology only requires collecting patients' body fluid samples. By utilizing tumor biomarkers such as ctDNA, it enable non-invasive monitoring and guides treatment while avoiding the injuries caused by invasive procedures. Although the clinical value of this technology varies across different application scenarios, and some of its uses are still in the research and exploration stage, it has demonstrated considerable application prospects in clinical practice.
The identification of non-invasive biomarkers that not only detect kidney cancer but also reflect clinically relevant tumor characteristics remains a major challenge in translational oncology. In this study, we aimed to identify specific FT-IR spectral wavenumbers in two biofluids: serum and urine and to directly correlate these spectroscopic markers with established clinicopathological parameters, including histological grade and tumor characteristics. By linking molecular-level spectral information with medical data, we sought to determine whether biochemical alterations detected in biofluids truly mirror histopathological findings and tumor biology. Second-derivative FT-IR spectra were collected from serum and urine samples obtained from patients with renal tumors and healthy controls. Multivariate exploratory analyses (PCA, UMAP), stability-based feature selection, and supervised classification with leave-one-patient-out cross-validation were performed independently for both biofluids. The most discriminatory and stable wavenumbers were identified and subsequently evaluated for their association with clinical variables. Urine spectra demonstrated stronger class separation and higher classification accuracy compared with serum, achieving up to 100% accuracy using SVM. Importantly, specific wavenumbers showed statistically significant correlations with histological grade in both serum (1160 cm-1, p = 0.0114) and urine (1300 cm-1, p = 0.0375), indicating that the detected spectral features reflect tumor aggressiveness rather than merely cancer presence. The most influential variables were located in the amide II and urea-related region (1530-1545, 1695 cm-1) for urine, and in phosphate, phospholipid and lipid carbonyl regions (844-980, 1160-1164, 1700-1780, 2984-2992 cm-1) for serum, consistent with locally excreted protein and urea changes in urine and systemic lipid-metabolism alterations in serum. These findings demonstrate that FT-IR spectroscopy of both serum and urine enables identification of spectral biomarkers that correlate with clinically meaningful pathological parameters. The integration of spectroscopic data with medical characteristics strengthens biological interpretability and supports the potential of FT-IR as a minimally invasive tool for kidney cancer detection and stratification.
Mammary tumors are among the most common neoplasms in dogs and cats, and malignant forms are clinically important in both species. Surgery remains the main treatment approach and may be combined with other treatment modalities, but advanced cases are often associated with recurrence and limited responsiveness to conventional therapies. Phytochemicals and plant extracts have received attention as potential adjuvant agents that can modulate pathways associated with oncogenesis and treatment resistance. Natural products are often accessible and relatively inexpensive, and their perception as well-tolerated agents may increase owner acceptance. Some plant extracts and phytochemicals, including Euphorbia royleana extract, celastrol, and homoharringtonine have shown potent preclinical activity in canine mammary tumor cell lines and xenograft models, but data for feline mammary tumors are still limited. However, their safety and efficacy depend on multiple factors such as the compound, dose, formulation, and species. Further studies are required for clinical translation, as species-specific pharmacokinetics significantly affect efficacy and safety. This review summarizes current knowledge on plant extracts and phytochemicals in canine and feline mammary tumors, focusing on their preclinical evidence, limitations, and future translational challenges in veterinary oncology.
Achieving optimal tumor eradication while minimizing off-target toxicity and enhancing patient recovery remains a central challenge in translational oncology. Traditional therapies such as radiotherapy and chemotherapy are associated with systemic toxicities and resistance, compromising outcomes. Photothermal therapy provides spatial targeting and a minimally invasive approach but risks collateral tissue damage, particularly to skin. We report an injectable, biodegradable PEG-tyrosine hydrogel with oxidative modification (PETyrO) designed for dual-function tumor photothermal therapy and post-treatment wound regeneration. PETyrO is prepared in two steps: (i) ring-opening polymerization of L-tyrosine N-carboxyanhydride (Tyr-NCA) monomers, followed by (ii) enzymatic oxidation using tyrosinase. The hydrogel forms at a final concentration of 100 mg/mL before injection. Owing to its phenolic groups, PETyrO exhibits pronounced reactive oxygen species (ROS) scavenging capacity, promoting epithelial regeneration at treatment sites. In summary, the melanin-like, biocompatible system shows minimal cytotoxicity, achieves a photothermal conversion efficiency of 36% at 808 nm and integrates ROS scavenging with wound-healing properties. More importantly, unlike traditional dopamine-based hydrogels, this peptide hydrogel features a well-defined structural framework and can degrade gradually in vivo. Through sequential control, it achieves tunable and repeatable structures and mechanical properties, increasing its potential for clinical translation. This multifunctional biomaterial offers a new paradigm for dual therapeutic capabilities.
Programmed cell death-ligand 1 (PD-L1) is best known as a membrane immune checkpoint; however, accumulating evidence indicates that PD-L1 can also localize to the nucleus, where it may exert PD-1-independent, cell-intrinsic functions in cancer. Emerging studies associate nuclear PD-L1 (nPD-L1) with aggressive disease, therapeutic resistance, and poor outcomes across multiple malignancies. In this review, we summarize current evidence regarding the regulatory mechanisms that may govern PD-L1 nuclear translocation, including post-translational modifications, stress-responsive signaling, and importin-dependent trafficking. We further discuss how nPD-L1 has been linked to adaptive programs involving DNA damage repair, metabolic rewiring, transcriptional regulation, and tumor microenvironment remodeling in context-dependent models. Clinically, nPD-L1 has potential relevance as a prognostic biomarker and as a candidate indicator of resistance to immunotherapy, radiotherapy, and chemotherapy, although prospective validation remains limited. We also highlight current challenges in detection and quantification, including the need for standardized multiplex imaging and digital pathology approaches. Finally, we discuss emerging therapeutic strategies aimed at disrupting PD-L1 nuclear trafficking or selectively targeting nuclear PD-L1-associated functions. Collectively, these findings support nPD-L1 as an important and potentially actionable dimension of PD-L1 biology that warrants further mechanistic and translational investigation.
Personalized medicine, driven by genomic insights, has catalyzed the emergence of innovative clinical trial designs such as basket and umbrella trials. These designs are particularly suited for evaluating targeted therapies in biomarker-defined subgroups and rare pediatric conditions where traditional trials face challenges of small sample sizes and disease heterogeneity. This systematic review aimed to characterize and synthesize the current literature on basket and umbrella trial designs in pediatric drug development, with a focus on their methodological, regulatory, and statistical aspects. A systematic search was conducted in the electronic databases PubMed, Scopus, and Web of Science to identify all literature related to basket and umbrella trials. A text mining analysis using unsupervised machine learning technique was performed with relevant articles to automatically identify the primary topics within publications on basket and umbrella trials. A systematic search of PubMed, Scopus, and Web of Science identified 1867 records. After screening and eligibility assessment, 28 studies were included in the final review. Topic modelling using Latent Dirichlet Allocation (LDA) was performed on 76 pertinent articles to identify dominant themes. Statistical convergence, topic coherence, and classification accuracy (> 85%) were validated. A systematic search of PubMed, Scopus, and Web of Science identified 1867 records. After screening and eligibility assessment, 28 studies were included in the final review. Basket trial designs were more prevalent than umbrella trials, particularly in early-phase oncology and rare disease research. Topic modelling using Latent Dirichlet Allocation (LDA) was performed on 76 relevant articles to identify dominant themes. Statistical convergence, topic coherence, and classification accuracy (> 85%) were validated. Basket and umbrella trials offer substantial advantages for pediatric drug development by increasing trial efficiency, enabling precision targeting, and supporting adaptive decision-making. Their success depends on robust statistical planning, careful use of Bayesian methods, and attention to regulatory guidance.
Cell membrane camouflage technology has been widely used as a key strategy to overcome the limitations of traditional synthetic nanoparticles in terms of blood circulation, immune clearance, and tumor accumulation. In this study, a hybrid membrane-coated CuS nanoplatform (CuS-BSA-PpIX@SR) modified with red blood cell membranes (RBCMs) and SKOV3 cancer cell membranes (CCMs) was constructed for targeted chemodynamic and sonodynamic synergistic therapy of ovarian cancer. The prepared CuS-BSA-PpIX@SR nanoplatform possessed a uniform spherical morphology, excellent dispersibility, and high structural stability. Moreover, the nanoplatform generated abundant ROS under ultrasound irradiation, effectively inducing oxidative stress and apoptosis in SKOV3 cells with enhanced sonodynamic activation efficiency. Furthermore, this nanosystem exhibits excellent tumor accumulation capacity, a longer circulating half-life, and significant tumor-suppressing effects in vivo, with its efficacy attributed to the synergistic effect of chemodynamics and sonodynamics. The CuS-BSA-PpIX@SR nanoplatform integrates multiple functions, including biomimetic membrane-mediated targeted delivery, effective activation of sonosensitizers, and enhancement of oxidative stress responses, achieving highly efficient, precise, and low-toxicity sonodynamic therapy (SDT) in an ovarian cancer model. This strategy not only provides innovative design ideas and technical support for sonodynamic therapy of deep tumors but also opens a new path for the translation of multifunctional biomimetic nanosystems into clinical precision oncology treatment.
Pancreatic cancer remains highly refractory to conventional therapies owing to its immunosuppression of the tumor microenvironment (TME) and dense stromal structure. Nanomaterial-based strategies offer promising avenues for integrating multimodal treatment and modulating immunosuppressive TME. Here, we utilize MXene nanosheets as the photothermal substrate, loading chlorophyll e6 (Ce6) as the photosensitizer, and coating with a hybrid membrane that is derived from cancer cells and thylakoid vesicles, which can achieve dual-mode photothermal and photodynamic therapy (PTT/PDT) under near-infrared light irradiation. Notably, the thylakoid membrane component facilitates in situ oxygen generation, effectively alleviates the hypoxia of the tumor, and significantly boosts reactive oxygen species (ROS) production for enhanced PDT. In vitro and in vivo research exhibit potent tumor suppression, exhibiting a 90% inhibition rate, achieved via synergistic hyperthermia and oxidative stress, accompanied by significant immunogenic cell death (ICD), dendritic cell (DC) maturation, and cytotoxic T-cell infiltration. Moreover, the combination of this nanoplatform with αPD-1 therapy can not only inhibit primary pancreatic tumor progression but also elicit abscopal effects and systemic antitumor immunity. This multifunctional nanoplatform presents a highly promising nanomedicine strategy for overcoming pancreatic cancer's therapeutic challenges by synergistically integrating phototherapy and immunotherapy, with clinical translational potential.