Cancers最新文献

Background/Objectives: Achieving complete, yet safe tumor resections are particularly challenging in pediatric oncology due to infiltrative tumor growth patterns, small patient size, and the close proximity to critical structures. Fluorescence-guided surgery (FGS) enhances visualization of anatomy, tissue perfusion, and tumor tissue in real time, potentially improving surgical precision. While widely explored in adults, its application in pediatric oncology remains limited. This review summarizes current evidence on FGS in pediatric oncology, with emphasis on the unique challenges inherent to this field. Finally, strategies to accelerate clinical translation and assess the potential clinical value are proposed. Methods: A narrative review of the literature was conducted using PubMed and Embase to identify English-language publications on FGS in pediatric oncology up to September 2025. Search terms included Fluorescence, Pediatrics, Neoplasms, and Surgery. Results: Studies commonly reported that indocyanine green (ICG) aids in lymph node mapping, hepatoblastoma resection, and visualization of vascular structures and tissue perfusion. However, its non-specific nature and lack of histopathological validation limits diagnostic precision in tumor imaging. Tissue-specific agents are being investigated in first-in-humans trials to improve sensitivity and specificity, and to identify ureters and nerves. Conclusions: In this review, the challenging roadmap for advancing FGS in pediatric oncology is presented. Closing current gaps will require coordinated efforts in target discovery, agent design, and clinical validation. If successful, FGS can evolve from a promising tool into an indispensable clinical technique that enhances surgical precision, reduces recurrence, and ultimately improves long-term outcomes for children with cancer.

The oral microbiome has become an emerging focus of oral cancer research, with growing evidence linking microbial communities to disease development, progression, and prognosis. However, there is limited consensus on optimal sampling strategies, storage methods, and analytical approaches. This narrative review critically evaluates current strategies for sampling, preservation, DNA extraction, sequencing, and data analysis in oral microbiome research related to oral cancer. We compared commonly used sampling methods, including saliva, oral rinse, swab, brush, and tissue biopsy, and reviewed preservation conditions, extraction kits, sequencing platforms, and analytical pipelines reported in recent oral microbiome studies. Sampling approaches affect microbial yield and site specificity. Saliva and oral rinse samples are convenient and noninvasive but may dilute lesion-specific microbial signals, whereas lesion-directed swabbing or brushing yields greater microbial biomass and biological relevance. Preservation media and storage temperature significantly influence microbial stability, and DNA extraction methods vary in their ability to remove host DNA. Although 16S rRNA gene sequencing remains the most common approach, shotgun metagenomics offers higher resolution and function insights but is still limited by clinical applicability. Differences in data pre- and post-processing models and normalization strategies further contribute to inconsistent microbial profiles. Given that oral mucosal sites differ markedly in structure and microenvironment, careful consideration is required to ensure that collected samples accurately represent the biological question being addressed. Methodological consistency across all workflow stages-from collection to analysis-is essential to generate reproducible, high-quality data and to enable reliable translation of oral microbiome research into clinical applications for cancer detection and risk assessment. Together, these insights provide a framework to guide future study design and support the development of clinically applicable microbiome-based biomarkers.

Background/Objectives: Targeted gene sequencing (TGS) for Comprehensive Genomic Profiling (CGP) use in sarcomas has recently increased in clinical practice. We report on TGS real-world data over a period of 3 years (2022-2025) at the IRCCS Istituto Ortopedico Rizzoli, with the aim of identifying potential actionable targets and providing therapeutic indications for advanced sarcoma patients. Methods: We analyzed 22 advanced sarcoma patients by using the VariantPlex Pan Solid Tumor kit panel, including 185 genes. In nine cases, saliva samples for germinal DNA analysis were available. Sequencing was performed on the NextSeq-500 Platform and analyzed with Archer Analysis software. The Cancer Genome Interpreter and OncoKB Database tools were used to find potential actionable targets. Results: We found the most frequent genetic variants, including missense, deletion, duplication, and delins, in the NOTCH4, AR, BARD1, MUC16, and ROS1 genes. Copy Number alterations affected the CDKN2A, CDKN2B, TP53, RHOA, MYC, CCND3, and DDR2 genes mainly in osteosarcoma samples. In four patients, longitudinal analyses of subsequent lesions showed the maintenance of most genomic alterations and enrichment in missense or splice variants in PMS2, SMARCA4, ARID1A, AKT1, BMPR1A, and PTEN, indicating the occurrence of tumor evolution. Germline variants subtraction identified the specific somatic tumor mutations. Advantages and disadvantages of our approach were considered in order to refine the analysis setting and better select possible actionable targets. Conclusions: Early access to genomic analyses, routine germline assessment, and broad gene panels would help in identifying possible targeted drugs with sufficient evidence of activity beneficial to each patient. In the clinical management of advanced sarcoma patients, when analyzing cost-effectiveness and sustainability, the role of the Molecular Tumor Board in the governance of the complexity introduced by mutational oncology should be considered.

Neoantigen-based immunotherapies harness somatic mutations as tumor-specific targets and represent a major advance in personalized cancer treatment. Since neoantigens are presented exclusively on cancer cells, they enable highly selective T-cell recognition with minimal off-tumor toxicity. Neoantigen vaccines are rapidly emerging as a versatile class of personalized cancer immunotherapies designed to prime tumor-specific T cells by targeting somatic mutations unique to each patient's tumor. Multiple types of neoantigen vaccines, using peptide, mRNA, and DNA, have shown feasibility, safety, and immunogenicity across diverse solid tumors. Emerging comparative data indicate that the vaccines using peptide-pulsed dendritic cells (DCs) elicit higher per-epitope CD8⁺ T cell responses than mRNA-based vaccines, likely due to more efficient class I presentation of synthetic peptides and ex vivo-loaded DCs. In contrast, mRNAs, despite their capacity of targeting multiple neoantigen peptides simultaneously, often induce CD4⁺-dominant responses due to immunodominance patterns during antigen processing. Recent clinical trials in melanoma, glioblastoma, pancreatic cancer, and other types of cancer have demonstrated not only robust immune activation but also encouraging relapse-free outcomes when administered in adjuvant settings. Treatment timing strongly influenced immune responsiveness; patients with early-stage disease or those vaccinated after surgical resection generally exhibit more preserved systemic immunity and greater vaccine-induced T cell expansion compared to those with advanced disease. Future progress will rely on improved neoantigen prediction, including incorporation of post-translationally modified antigenic targets and acceleration of manufacturing pipelines to ensure timely, personalized vaccine delivery. Collectively, neoantigen vaccines offer substantial promise for integration into next-generation cancer treatment strategies.

Introduction: Prompt diagnosis and differentiation between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) are essential in the treatment of bladder cancer. Inflammation-based biomarkers have recently emerged as potential tools for improving cancer diagnostics and prognostication. This study aims to evaluate the potential value of the Systemic Inflammation Index (SII), Systemic Inflammation Response Index (SIRI), Pan-immune Inflammation Value (PIV), and Platelet-to-Lymphocyte Ratio (PLR) as predictors of muscle-invasive disease.

Materials and methods: Analyzed data included 310 bladder tumors. The SII, SIRI, PIV, and PLR were calculated from pre-TURBT complete blood-count results. Differences in inflammatory markers between pathological stages (pTa-pT4) were examined using ANOVA with Tukey's post hoc testing. Optimal cutoff values for distinguishing NMIBC from MIBC were identified using ROC curve analysis and Youden's J statistic. Logistic regression models incorporating age, sex, the number of recurrences, and each inflammatory index were developed to evaluate their predictive performance in patients treated with curative intent.

Results: All investigated inflammation indices significantly differed across tumor stages (p < 0.001), with lower values observed in pTa tumors compared with muscle-invasive disease. Determined cutoff values for muscle-invasive disease were 865.63 for SII, 2.02 for SIRI, 579.28 for PIV, and 166.35 for PLR. Logistic regression models demonstrated promising diagnostic performance, achieving AUC values of 0.812 (SII), 0.816 (SIRI), 0.821 (PIV), and 0.795 (PLR); sensitivity and specificity were 76% and 75% for SII, 79% and 77% for SIRI, 80% and 72% for PIV, and 88% and 59% for PLR.

Discussion: The presented results indicate that inflammation-based indices vary meaningfully between bladder cancer stages and may be utilized in early identification of muscle-invasive disease. As inexpensive and widely available biomarkers, they offer potential value in the evaluation of suspected MIBC before the final pathology report and could enhance the diagnostic process.

Immunotherapy (IT) and especially immune checkpoint blockade (ICB) changed the therapeutic approach in non-small cell lung cancer (NSCLC). Nevertheless, primary or secondary resistance and a percentage of long responders and survivors have been observed. The aim of this study is to gain a deeper understanding of the complex mechanisms of primary and secondary resistance to IT, involving tumor cells, the tumor microenvironment (TME), and the host, in order to find strategies to overcome it. With this aim in mind, a search for key words has been performed to identify relevant evidence in the literature. The most widely used approach is the combination of IT with chemotherapy (CT) and/or radiotherapy (RT), relying on the synergistic effect on the enhancement of immunogenic cell death. Since a dual role has been observed, a lot of questions are yet to be answered regarding the complex effect of these therapies, especially on the TME. Preclinical and clinical studies investigate the best sequencing and timing of chemoradiation with IT, and the optimal RT volumes, sites, and dose/fractionation regimens to favor immune stimulation over suppression on the TME. Moving forward, multiple agents addressing coinhibitory or costimulatory receptors on immune or tumor cells are under evaluation. The huge potential of combination therapies becoming apparent. Questions regarding targets, selection of patients, and time and sequence of administration are yet to be answered, considering the complex mechanisms of resistance. Dynamic biomarkers to guide personalized treatment decisions are needed.

Background: Visual impairment is linked to a broad spectrum of health conditions. Nevertheless, there is an absence of large cohort studies investigating cancer risk in the visually impaired compared to seeing controls. The aim of this study was to investigate whether visually impaired adults have an increased risk for various types of cancer, compared to seeing controls. Methods: This was a retrospective cohort study comparing visually impaired adults aged 40 and over and 1:5 matched controls (by sex, birth year, and county of residence), between 2002 and 2018. Data were extracted from the Swedish National patient Registry, Statistics Sweden and from the Swedish Cause of Death Registry. A total of 48,493 adult Swedish men (44%) and women (56%), with a median age of 77 years (IQR: 64-86), with various degrees of visual impairment, from mild to total blindness, and 242,465 matched controls were followed up for a median of 5.1 (IQR 2.9-8.6) and 6.0 (IQR 3.6-9.8) years, respectively. The main outcomes included overall cancer incidence and incidence of different types of cancer. Results: Data analysis showed that visually impaired adults had an 18% significantly increased risk of any cancer (HR 1.18, 95% CI 1.16-1.20) when compared to seeing controls. The risk was also significantly increased for most cancers, with HRs ranging from 2.59 (95% CI 2.21-3.03) for brain cancer to 1.19 (95% CI 1.11-1.27) for breast cancer. No interaction was observed between cancer of any type and sex (p = 0.47). An elevated risk for all cancers in the visually impaired was observed across all age-groups: HR of 1.37 (95% CI 1.30-1.43) for ages 40-64, HR 1.17 (95% CI 1.13-1.20) for ages 65-79, and HR 1.11 (95% CI 1.08-1.15) for ages over 80. The risk of death was 60% higher among the cases compared to controls (HR 1.60, 95% CI 1.58-1.63). Conclusions: In this retrospective study of older adults, visual impairment was associated with increased cancer risk both overall and for specific types of cancer, in both sexes and across different age divisions of the cohort. These findings indicate the need for adjustments in health care polices in order to ensure equity in medical services.

Background/Objectives: Non-melanoma skin cancer, which includes cutaneous squamous cell carcinoma (cSCC), ranks as the 5th most common cancer globally with high morbidity and more total deaths than melanoma despite having a lower mortality rate. While most cSCC cases can be treated with surgery, locally advanced, metastatic, and high-risk cSCC tumors are associated with a worse prognosis with higher rates of recurrence and require multimodality therapy. However, there is limited data on animal models of cutaneous squamous cell carcinoma for the use of combinatory immunotherapy and radiation. Methods: In this study, spontaneously generated tumors using DMBA/TPA were treated over three weeks with either IgG control, anti-PD1 antibody monotherapy, 8 Gy of localized radiation, or a combination of anti-PD1 and 8 Gy of radiation followed by anti-PD1 therapy. Results: We found that while anti-PD1 therapy showed a trend toward slowed tumor growth compared to controls, this difference was not statistically significant (p = 0.0775), with most mice showing continued tumor progression. Preliminary histological analysis suggested that anti-PD1 treatment increased CD8+ T cell infiltration, and the addition of radiation further enhanced CD8+ responses but added greater variability. A pathologic review revealed that irradiated tumors were associated with fibroblastic spindle-like cell morphology. Conclusions: This animal model represents a potential preclinical model for studying CSCC with limited responses to immunotherapy to understand potential mechanisms of resistance.

Background: Radiomics provides a non-invasive approach for predicting lymph node metastasis (LNM) in cervical cancer, but conventional whole-tumor analysis often overlooks intratumoral heterogeneity. Methods: This study aimed to develop and validate an MRI-based habitat radiomics model for preoperative prediction of pelvic LNM in early-stage cervical cancer. Tumor regions were delineated on diffusion-weighted imaging, and intratumoral habitats were generated using unsupervised K-means clustering. Radiomic features were extracted from whole tumors and habitat subregions, combined with clinical variables, and selected using correlation analysis and LASSO regression. Four models-clinical, conventional radiomics, habitat radiomics, and combined-were constructed and evaluated. Results: In internal validation, the combined model achieved the best performance (AUC = 0.895), outperforming the clinical (AUC = 0.799), conventional radiomics (AUC = 0.611), and habitat models (AUC = 0.872). Calibration and decision curve analyses demonstrated good agreement and clinical utility. Conclusions: Integrating habitat-based radiomics with clinical factors significantly improves the preoperative prediction of LNM, providing a robust and clinically applicable tool for individualized management of cervical cancer patients.

The journal retracts the article, "The Small Molecule Ephrin Receptor Inhibitor, GLPG1790, Reduces Renewal Capabilities of Cancer Stem Cells, Showing Anti-Tumour Efficacy on Preclinical Glioblastoma Models" [...].