Journal of Cancer Research and Clinical Oncology最新文献

Background/objectives: Pancreatic cancer surgery frequently results in positive margins and local recurrence despite multimodal treatment. This study evaluated whether combining neoadjuvant stereotactic body radiotherapy (SBRT) with intraoperative electron radiotherapy (IOeRT) during resection could improve local control and surgical outcomes.

Methods: A retrospective analysis was performed on 15 patients with resectable or borderline resectable pancreatic adenocarcinoma treated between 2021 and 2023. All patients received image-guided, motion-managed SBRT (35-40 Gy/5 fractions to PTV_high; 25 Gy/5 fractions to PTV_low) followed by surgical resection and IOeRT (median 10 Gy; 12 Gy when margins were at risk). Toxicities were graded by CTCAE v5.0 and postoperative complications by Clavien-Dindo criteria. Follow-up included imaging and CA 19-9 every 3 months. Survival was estimated using Kaplan-Meier analysis.

Results: Mean patient age was 66 years; 60% had tumors in the pancreatic body and 40% in the head. Two-thirds were borderline resectable and received neoadjuvant chemotherapy. Margin-negative resection was achieved in 86.7%, including two complete pathologic responses in BRCA2-mutated tumors. Median overall and progression-free survival were 30 and 16 months, respectively. One patient (6.7%) developed isolated local recurrence, while distant metastases occurred in over half. Toxicities were mainly grade 1-2 fatigue, nausea, or pain; surgical complications were grade 1-2 in 53%, grade 3 in 7%, and grade 5 in 7%.

Conclusions: Neoadjuvant SBRT with IOeRT during pancreatic cancer resection is feasible, achieves high rates of negative margins, and provides promising local control. Distant progression remains the dominant mode of failure.

Background: Brahmi (Bacopa monnieri) plant preparation (BPP) has been recognizedfor its immunomodulatory capabilities, but its molecular and epigenetic effects onimmune cells in non-small cell lung cancer (NSCLC) remain unknown.

Objective: Thisstudy investigated the way BPP influenced the molecular phenotype and functionalprofile of monocyte-derived dendritic cells (DCs) derived from an NSCLC patient anda healthy donor.

Result: BPP treatment enhanced DC maturation, as demonstrated byelevated levels of CD1d and co-stimulatory molecules (CD80/CD86), and conditionedsupernatants that efficiently activated autologous T cells. BPP increased proinflammatorysignaling molecules STAT1, STAT2, STAT4, and total NF-κB, whiledecreasing STAT3, STAT5, STAT6, and the DNA-repair protein DNAPKcs.Transcriptional analysis indicated a Th1-oriented immune program, characterized bythe up-regulation of TBX21, IFNG, and TP53, alongside the down-regulation ofGATA3, FOXP3, RORC, IL10, and MYC. Chromatin profiling revealed an enrichmentof H3K4me3 and H3K14ac, alongside p53 recruitment at the IFNG/TBX21 loci,accompanied by diminished levels of H3K27me3, HDAC2, and reduced promoteroccupancy by c-Myc and NF-κB. BPP enhanced the secretion of IFN-γ, IL-2, and TNF-α while diminishing IL-4, IL-10, and IL-17, establishing a pro-inflammatoryenvironment indicative of Th1-type polarization. Co-culture experiments validatedincreased cytotoxic T-cell activity against A549 cells (NSCLC cells), assessed throughLDH release and statistically confirmed via ANOVA with Tukey post-hoc analysis.

Conclusion: Overall, these findings demonstrate the ability of BPP to influence dendritic and T-cell responses in NSCLC via coordinated transcriptional and chromatinremodelling activities.

Purpose: With increasing reliance on large language models (LLMs) for health information, this study evaluated reliability and quality, understandability, actionability, readability and misinformation risk of responses from LLMs to oral health concerns and oral side effects in head and neck cancer (HNC) patients.

Methods: Frequently asked questions on oral health and HNC therapy side effects were identified via ChatGPT-GPT-4-turbo and Gemini-2.5 Flash, then submitted to eight LLMs (ChatGPT-GPT-4-turbo, Gemini-2.5 Flash, Microsoft Copilot, Perplexity, Chatsonic, Mistral, Meta AI-Llama 4, DeepSeek-R1). Responses were assessed using DISCERN and modified DISCERN instruments (reliability and quality), Patient Education Materials Assessment Tool (PEMAT [understandability and actionability]), Flesch-Reading-Ease-Score (FRES [readability]), misinformation score, citations, and wordcounts. Statistical analysis was done by Scheirer-Ray-Hare-test followed by Dunn's post-hoc-tests and Bonferroni-Holm correction (p < 0.05).

Results: A total of 40 questions belonging to 12 oral health-related categories were identified. Statistically significant differences between LLMs were found for DISCERN, modified DISCERN, PEMAT-understandability, PEMAT-actionability, FRES, and word counts (p < 0.001). Median DISCERN and modified DISCERN scores amounted from 47.0 (ChatGPT-GPT-4-turbo) to 59.0 (Perplexity, Chatsonic) and from 2.0 (Gemini-2.5 Flash, Mistral) to 5.0 (Perplexity) indicating good to fair reliability. LLMs were understandable (median PEMAT-understandability scores ≥ 75.0), but provided limited specific guidance (median PEMAT-actionability scores ≤ 40) and used complex language (median FRES ≤ 40.2). Misinformation risk was generally low and not statistically significant among LLMs (p = 0.768).

Conclusion: Despite a low overall misinformation risk, deficits in actionability highlight the need for cautious integration of LLMs into HNC patient education.

The intratumoral microbiota has emerged as a critical modulator of gastrointestinal (GI) tumour pathogenesis, influencing cancer initiation, progression, and treatment response. Recent studies have revealed that tumour-resident microbes, such as Fusobacterium nucleatum (F. nucleatum) and Bacteroides fragilis, contribute to metabolic reprogramming, immune evasion, and metastatic spread via mechanisms including microbiota-derived metabolites, induction of epithelial-mesenchymal transition, and conditioning of the premetastatic niche. Advances in multiomics technologies have enabled the precise characterization of microbial composition and function within the tumour microenvironment, revealing prognostic and predictive microbial signatures. Furthermore, emerging evidence highlights the potential of targeting the intratumoral microbiota to enhance conventional therapies and immunotherapies. This review summarizes key developments in understanding the role of the intratumoral microbiota in GI cancers and discusses future directions for translating these insights into clinical applications.

Purpose: This study evaluated the safety and preliminary efficacy of zolbetuximab plus chemotherapy in patients with claudin 18 isoform 2 (CLDN18.2)-positive advanced gastric cancer (AGC).

Methods: This single-institutional retrospective study enrolled patients with HER2-negative CLDN18.2-positive AGC who were treated with zolbetuximab plus chemotherapy between July 2024 and August 2025.

Results: The cohort included 50 patients with a median age of 63 years (range 30-83; 44% male). The primary tumor location was the stomach in 86% of the patients. Meanwhile, 26% of the patients underwent prior gastrectomy. The PD-L1 combined positive score was < 5 in 87% of patients. Among 24 patients with measurable lesions at baseline, the objective response and disease control rates were 66.7% and 87.5%, respectively. After median follow-up of 7.3 months, median progression-free survival and the duration of response were 6.7 [95% confidence interval (CI) 5.3-10.7] and 6.7 months (95% CI 4.7-10.2), respectively. Grade ≥ 3 treatment-emergent adverse events occurred in 62% of the patients, most commonly hypoalbuminemia (22%), neutrophil count decreased (22%) and anorexia (12%). Subsequent treatment was received by 83% of the patients.

Conclusions: Zolbetuximab plus chemotherapy was administered to real-world patients with CLDN18.2-positive AGC with acceptable safety profiles and showed preliminary antitumor efficacy. Nevertheless, some adverse events warrant careful monitoring.

Background: Thyroid cancer (TC) is one of the most prevalent endocrine malignancies, and its recurrence presents a major clinical challenge that can adversely affect patient prognosis and treatment outcomes. Despite the progress in diagnostic methods, traditional statistical models still face limitations in accurately predicting TC recurrence due to the intricate interactions between clinical and pathological factors.

Methods: To address this challenge, the study presented a novel stacking ensemble learning framework for TC recurrence prediction. The dataset included a total of 383 patients, comprising 108 recurrence and 275 non-recurrence cases, and was stratified into training set (n = 268) and testing set (n = 115) using a 70:30 ratio. The proposed stacking framework integrated three heterogeneous base learners, namely Stochastic Gradient Descent (SGD), Extra Trees (ET), and Decision Trees (DT) with eXtreme Gradient Boosting (XGBoost) as the meta learner. The hyperparameter optimization of various learners was performed through 5-fold cross-validation on the training set. The model performance was evaluated on testing set using accuracy, precision, recall, F1-score, AUC, and Brier score (BS). To enhance the model's interpretability, the Shapley Additive Explanations (SHAP) method was utilized to identify the overall top influential factor and provide local interpretation for specific individual patient based model outcome.

Results: The proposed stacking model achieved accuracy of 96.52%, precision of 96.67%, recall of 90.62%, and F1-Score of 93.55%, AUC of 0.9921 on the testing set. The SHAP analysis revealed the top 5 critical factors to TC recurrence, including treatment response, age, N-stage, risk stratification, and adenopathy. Furthermore, an interactive and user-friendly prediction tool, TCCheck, was developed based on optimized stacking model, accessible online at https://tccheck-prediction-tool.streamlit.app/ .

Conclusion: The study presented an effective and interpretable stacking ensemble learning framework for predicting TC recurrence. By deploying the proposed framework as a web prediction tool, it enables explainable and individualized clinical decision support, thereby enhancing its translational value in real-world settings. Furthermore, the framework serves as a methodological reference for recurrence prediction in other cancer types.

Background: Melanoma, a highly metastatic and treatment-resistant malignancy, urgently requires novel therapeutic strategies. Puerarin, a natural isoflavone with established anti-tumorigenic effects in diverse cancers, remains underexplored in melanoma despite its potential to modulate melanogenesis and oxidative stress. This study investigates puerarin's spatial targeting mechanisms in melanoma to elucidate its therapeutic specificity.

Methods: A multi-omics approach integrating single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and structure-based docking plus normal-mode analysis was employed. Spatial domain analysis identified puerarin-responsive malignant cell clusters, while molecular docking and protein-ligand simulations prioritized CD44 as a candidate receptor. Functional validation included extracellular matrix (ECM) signaling pathway analysis, spatial colocalization studies, and in vitro experiments.

Results: Spatial analysis showed enrichment of puerarin-related signals in malignant-cell-dominated domains. ECM ligands (collagens, fibronectin, laminins) that signal through CD44/SDC1 were concentrated in these domains, where CD44 was overexpressed relative to surrounding compartments. Molecular modeling suggested CD44, a cell-surface receptor overexpressed in melanoma cells, as a putative mediator of puerarin's effects on these pathways. In vitro experiments further supported CD44's role in modulating puerarin-responsive domains.

Conclusion: These observations are hypothesis-generating and provide a potential direction for future research on whether CD44 mediates puerarin's spatial effects in melanoma.

Purpose: Genetic mutations contribute to around 10% of breast and 25% of ovarian cancers, with one third of patients having a familial cancer history. The German Consortium for Familial Breast and Ovarian Cancer was founded in 1996 to improve care for these patients. Certification of cancer centers, introduced in 2004, has been linked to improved survival rates and ensures adherence to evidence-based standards. This study investigates changes in care structures and quality before and after the initial certification of the HBOC center at the University Hospital Erlangen, certified from 2021 on.

Methods: This retrospective study analyzed patient data from January 2018 to December 2023 at the certified Hereditary Breast and Ovarian Cancer center at the University Hospital Erlangen. Eligibility for genetic counseling and germline testing followed the German Cancer Society criteria. After informed consent, Next Generation Sequencing was performed, and variants were classified according to Human Genome Variation Society and American College of Medical Genetics and Genomics standards. Medical histories and genetic results were recorded in electronic case report forms.

Results: From 2018 to 2023, a total of 2694 genetic tests were performed, increasing from 962 pre-certification to 1732 post-certification (+ 180%). Testing among affected female patients doubled. Genetic testing in breast cancer patients increased from 551 to 1,04, while testing for ovarian carcinoma rose from 117 to 159. Variants of uncertain significance were identified in approximately 9% of cases during both periods. Pathogenic findings were observed in 14.3% of cases pre-certification (with 9.2% involving BRCA1/2 mutations) and 11.5% post-certification (6.4% BRCA1/2 mutations). Enrollment in the intensified surveillance program (IBCS) increased by 182.5%, accompanied by a rise in recommendations for risk-reducing surgeries.

Conclusion: Certification of medical institutions ensures high-quality, evidence-based patient care and increases the utilization of preventive and counseling services, particularly for Hereditary Breast and Ovarian Cancer. Further studies are needed to confirm the long-term impact and necessity of certification.

Background: Clear cell renal cell carcinoma (ccRCC) is a major type of kidney cancer, making up about 80% of cases, with advanced stages showing low survival rates. Current treatments face challenges like toxicity and drug resistance. Studies indicate lactate, through the Warburg effect, promotes an immune-suppressive tumor microenvironment (TME), prompting the development of the LAC-TME classifier using machine learning to predict outcomes and personalize treatment.

Methods: The study used data from TCGA-KIRC set and E-MTAB-1980 set, analyzing gene expression, mutations, and clinical data. It employed differential expression analysis, immune infiltration assessment, and 101 machine learning algorithms to build the classifier, integrating lactate-related genes and TME features, with predictive capability verified.

Results: The LAC-TME classifier, constructed by integrating 9 lactate-related differentially expressed genes and TME cells, demonstrated high predictive accuracy (C-index of 0.92 in the training set and 0.73 in the validation set). Patients were categorized into three groups: Lactate^low + TME^low (best prognosis), Lactate^high + TME^high (poorest prognosis), and a mixed group. This classifier can predict 1- to 5-year survival rates, with an AUC of 0.88-0.92. Notably, the Lactate^high + TME^high subgroup was associated with immunosuppression and poor response to immunotherapy. As the core lactate-related gene of the LAC-TME classifier, the knockdown of LGALS1 significantly inhibits the proliferation and migration of ccRCC cells, verifying the biological rationality of the classifier.

Conclusion: The LAC-TME classifier, integrating metabolic and immune data, offers a new tool for ccRCC prognosis and treatment guidance. Further validation is needed to confirm its clinical potential, reflecting the ongoing need for robust medical research.

Objective: This systematic review and meta-analysis aimed to assess the prognostic value of pre-treatment hematological parameters, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV), in patients with oral squamous cell carcinoma (OSCC).

Methods: A systematic search of PubMed, Embase, Scopus, Web of Science, ScienceDirect, and Google Scholar was conducted until April 2025. We included English-language observational studies reporting associations between NLR, PLR, MPV, and survival or clinicopathological outcomes in OSCC. Data extraction and risk of bias assessment using the Newcastle-Ottawa Scale were performed independently by two reviewers. Hazard ratios (HRs) and odds ratios (ORs) were pooled using a random-effects model. The certainty of evidence was evaluated using the GRADE.

Results: Thirty-five studies (approximately 7940 patients) were included. A high NLR was associated with worse overall survival (pooled HR 1.59, 95% CI 1.32-1.92) and disease-free survival (HR 1.66, 95% CI 1.31-2.10). PLR showed similar associations with overall survival (HR 1.58, 95% CI 1.29-1.94) and disease-free survival (HR 1.50, 95% CI 1.18-1.90). Between-study heterogeneity was moderate to high in this study. MPV findings were inconsistent and not pooled.

Conclusions: Elevated NLR and PLR correlate with poorer outcomes in OSCC, with effect sizes varying by study design and cut-off selection. These blood-based indices may aid in risk stratification; however, prospective validation with standardized thresholds is required.