Current oncology最新文献

The use of deep learning radiomics to predict whether advanced prostate cancer (PCa) will progress within two years after treatment has been validated, yet there remains a lack of research on estimating time to progression. Patients were enrolled from October 2017 to March 2024. One hundred and eighty-two patients with advanced PCa diagnosed through ultrasound-guided systematic prostate biopsy were enrolled. A deep learning-based radiomics model for predicting progression was firstly developed using pretreatment MR apparent diffusion coefficient (ADC) maps, and the performance of manual (ROIref) versus AI-derived (ROIai) tumor segmentations was compared. Then, survival analysis was performed to compare ROIref-based and ROIai-based radiomics-predicted probabilities in the risk stratification. The area under the receiver operating characteristics curve (AUC) was used to estimate the model efficacy. The model achieved high AUC values for progression prediction in test sets (ROIref: 0.840, ROIai: 0.852). No significant difference was observed between ROIai-based and ROIref-based approaches (ΔAUC = 0.012, p = 0.870) in the test set. Both ROIref-predicted and ROIai-predicted probabilities independently predicted progression in multivariate Cox proportional hazard regression models (p < 0.001) and stratified patients into distinct survival groups (log-rank p < 0.001). Decision curve analysis confirmed equivalent clinical utility across thresholds (0.1-0.6), with net benefit exceeding the "treat all" and "treat none" strategies. In conclusion, deep learning-based radiomics models could effectively predict advanced PCa progression, with AI-derived tumor annotations performing equally to manual expert ones.

Background: Pancreatic cancer is the least survivable malignancy, with five-year survival below 10%. Its vague, non-specific symptoms contribute to late diagnosis and poor outcomes. Targeted education for healthcare professionals, students, patients, carers, and the public may improve awareness, confidence, and early help-seeking. This scoping review aimed to map and synthesize peer-reviewed evidence on pancreatic cancer education, identifying intervention types, outcomes, and gaps in knowledge. Methods: A scoping review was undertaken using the Joanna Briggs Institute (JBI) framework and the Arksey and O'Malley framework and reported in accordance with PRISMA-ScR guidelines. The protocol was registered on the Open Science Framework. Four databases (MEDLINE, Embase, CINAHL, PsycINFO) were searched for English-language, peer-reviewed studies evaluating educational interventions on pancreatic cancer for healthcare students, professionals, patients, carers, or the public. Grey literature was excluded to maintain a consistent methodological standard. Data were charted and synthesised narratively. Results: Nine studies (2018-2024) met inclusion criteria, predominantly from high-income countries. Interventions targeted students and professionals (n = 3), patients (n = 2), the public (n = 2), or mixed groups (n = 2), using modalities such as team-based learning, workshops, virtual reality, serious games, and digital animations. Four interrelated themes were identified, encompassing (1) Self-efficacy; (2) Knowledge; (3) Behavior; and (4) Acceptability. Digital and interactive approaches demonstrated particularly strong engagement and learning gains. Conclusions: Pancreatic cancer education shows clear potential to enhance knowledge, confidence, and engagement across diverse audiences. Digital platforms offer scalable opportunities but require quality assurance and long-term evaluation to sustain impact. The evidence base remains limited and fragmented, highlighting the need for validated outcome measures, longitudinal research, and greater international representation to support the integration of education into a global pancreatic cancer control strategy. Future studies should also evaluate how educational interventions influence clinical practice and real-world help-seeking behaviour.

Evaluation of pituitary neuroendocrine tumors remains complex depending on the exact growth pattern, involvement of critical neurovascular structures, pituitary function and endocrinological activity of the tumor. A predominant growth into the sphenoid sinus and clivus poses specific challenges. We reviewed 557 surgeries for pituitary neuroendocrine tumors in an endonasal endoscopic technique performed between 1 January 2015 and 31 August 2025 to identify 13 cases (2.3%). Clinical, radiological and surgical data were selected by chart review. Thirteen cases aged from 31 to 68 years with almost exclusively non-functioning or clinically silent tumors (92%) were identified. Clival infiltration was restricted to the dorsum sellae in 2/13 (15%), spread to the floor of the sphenoid in 6/13 (46%) and extended inferior to the sphenoid in 5/13 (38%) cases with a high rate of cavernous sinus (62%) and sphenoid sinus infiltration (69%). Complete resection was achieved in 31%, and the residual tumor was clival/sphenoidal in 5/13 cases or within the cavernous sinus in 6/13 cases. The diaphragma sellae was reported to be intact in 92% of cases, and postoperative transient arginine vasopressin deficiency did not occur. Pituitary neuroendocrine tumors predominantly growing below the sella and infiltrating the clivus and sphenoid present specific challenges with a high rate of preoperative pituitary insufficiency, frequent cavernous sinus infiltration and postoperative tumor residuals in the cavernous sinus, sphenoid bone and clivus which are sometimes difficult to delineate. The surgical approach must be tailored specifically to treat the clival infiltration zone to reduce the risk of recurrence.

The dramatic shift in human behavior from hunter-gatherer to modern lifestyles has led to a systematic disruption of the human circadian cycle. Contributors include night-shift work, jet lag, and less intuitive but widespread factors, such as exposure to artificial light at night and irregular eating schedules. Circadian disruption is classified as a Group 2A carcinogen by the International Agency for Research on Cancer (IARC). Hepatocellular carcinoma (HCC) is the third most deadly cancer worldwide, with a rising prevalence in Western countries, largely driven by increasing rates of obesity and steatotic liver disease-associated hepatocarcinogenesis. Emerging evidence suggests that circadian disruption plays a significant role in HCC pathogenesis. Several genes involved in metabolism, cell survival, and immunosurveillance are under the control of circadian rhythms. Experimental preclinical data and epidemiological studies have indicated a strong association between circadian disruption and HCC development. Moreover, molecular signatures related to circadian regulation appear to accurately predict the prognosis of patients with HCC. The concept of chronotherapy is also gaining interest, with studies suggesting improved immunotherapy effectiveness when immune checkpoint inhibitors are administered in the morning. This review summarizes the current literature on the impact of circadian disruption on HCC pathogenesis, prognosis, and treatment.

Immunohistochemistry (IHC) is essential for diagnostic, prognostic, and predictive biomarker assessment in oncology, but manual interpretation is limited by subjectivity and inter-observer variability. Machine learning (ML), a computational subset of AI that allows algorithms to recognise patterns and learn from annotated datasets to make predictions or decisions, has led to advancements in digital pathology by supporting automated quantification of biomarker expression on whole-slide images (WSIs). This review evaluates the role of ML-assisted IHC scoring in the transition from validated biomarkers to the discovery of emerging prognostic and predictive IHC biomarkers for genitourinary (GU) tumours. Current applications include ML-based scoring of routinely used biomarkers such as ER/PR, HER2, mismatch repair (MMR) proteins, PD-L1, and Ki-67, demonstrating improved consistency and scalability. Emerging studies in GU cancers show that algorithms can quantify markers including androgen receptor (AR), PTEN, cytokeratins, Uroplakin II, Nectin-4 and immune checkpoint proteins, with early evidence indicating associations between ML-derived metrics and clinical outcomes. Important limitations remain, including limited availability of training datasets, variability in staining protocols, and regulatory challenges. Overall, ML-assisted IHC scoring is a reproducible and evolving approach that may support biomarker discovery and enhance precision GU oncology.

This study evaluated whether a composite index combining the systemic immune-inflammation index (SII) and prognostic nutritional index (PNI), the coSII-PNI score, enhances prognostic prediction in head and neck cancer. We retrospectively evaluated 166 patients who underwent curative surgery between 2015 and 2023. Patients were stratified into three groups according to the coSII-PNI score (range, 0-2) derived from preoperative blood data. The optimal cutoff values for SII and PNI were 743 and 49, respectively. A significant correlation was observed between the SII and PNI (r = -0.386, p < 0.01). Patients with a high coSII-PNI score (low SII + high PNI) showed significantly better disease-free and overall survival than those with lower scores (both p < 0.01). The areas under the curve for predicting prognosis were 0.649 for SII, 0.717 for PNI, and 0.730 for the coSII-PNI score. These findings indicate that integrating systemic inflammation and nutritional status improves prognostic accuracy compared with either index alone. Therefore, the coSII-PNI score may serve as a simple, practical preoperative biomarker for risk stratification in patients with head and neck cancer.

Background: Liver cirrhosis increases perioperative risk in colorectal cancer surgery, yet data on long-term outcomes remain limited. In this study, we evaluated postoperative morbidity, mortality, and survival in cirrhotic patients. Methods: In this single-center retrospective cohort, 53 cirrhotic patients undergoing elective colectomy or proctectomy (2011-2022) were propensity score-matched 1:1 with non-cirrhotic controls. Perioperative variables, complications, and survival were analyzed. Subgroup analyses were performed for right hemicolectomy and non-right hemicolectomy procedures. Kaplan-Meier and logistic regression analyses were implemented to assess outcomes and risk factors. Results: Cirrhotic patients had higher preoperative MELD-Na scores and lower albumin and hemoglobin levels. They experienced greater blood loss, longer operative times, more ICU admissions, and higher rates of major complications (18.9% vs. 3.8%, p = 0.01). Mortality was higher at in-hospital (7.5% vs. 0%), 3-month (9.4% vs. 0%), and 60-month (66% vs. 28.3%) intervals, and these patients' overall survival was shorter (70.7 vs. 116.8 months, p < 0.001). The subgroup analysis showed that the adverse impact of cirrhosis persisted for both right hemicolectomy and non-right hemicolectomy procedures, with significantly worse long-term survival in cirrhotic patients. Postoperative complications after right hemicolectomy did not differ significantly between groups. Among cirrhotic patients, Child-Turcotte-Pugh class B predicted worse survival than class A (40.1 vs. 84.8 months, p = 0.006). Preoperative hypoalbuminemia (<3.5 g/dL) independently predicted long-term mortality (HR = 3.93). Conclusions: Elective colorectal surgery in patients with cirrhosis is associated with increased perioperative complications and significantly reduced long-term survival. However, postoperative outcomes after right hemicolectomy in cirrhotic patients were comparable to those of non-cirrhotic patients, despite their persistently poorer long-term survival. Optimization of nutritional status and careful preoperative assessment of hepatic reserve are essential to improving outcomes in this high-risk population.

Pembrolizumab, an anti-PD-1 monoclonal antibody, showed promising results in the treatment of different types of solid tumors and generally an improvement in overall survival and patients' outcome. However, as a drug that targets the immune system to enhance the anti-tumor response, it simultaneously increases the risk of autoimmune reactions, producing immune-related adverse events (irAEs). These irAEs might involve any body organ, and in some cases may lead to treatment discontinuation. In this article, we discuss two cases of triple-negative breast cancer (TNBC) patients, who developed irAEs during the course of neoadjuvant pembrolizumab, highlighting the mechanism of the reactions, possible clinical manifestations, and potential management.

Background: Chemotherapy-induced nausea and vomiting (CINV) is a common treatment-related side effect that has a detrimental effect on the quality of life of patients with cancer and may lead to dose reductions or discontinuation of chemotherapy. This meta-analysis aims to explore the efficacy and safety of olanzapine plus triple antiemetic therapy for prevention of delayed-phase platinum-based CINV. Methods: Electronic databases (five English databases: (I) PubMed, (II) ScienceDirect, (III) The Cochrane Library, (IV) Scopus, and (V) EMBASE, and two Chinese databases: China National Knowledge Infrastructure and Wanfang Database) were searched for trials that evaluated the effectiveness and safety of olanzapine plus triple antiemetic in preventing platinum-based CINV. Efficacy was no nausea, complete control, and complete response (CR) rates in the acute, delayed, and overall phases after chemotherapy. Data were analyzed using the random effects model and fixed effects model. Results: A total of 18 trials involving 3110 patients were identified, including 9 controlled trials and 9 single-arm trials. The meta-analysis of nine studies, which showed significant heterogeneity (p = 0.002, I² = 67%), demonstrated that the olanzapine (OLN) group had a significantly higher rate of delayed CR compared to the control group (OR: 2.33, 95% CI: 1.57-3.46, p < 0.00001). Compared with the Without OLN group, the With OLN group had a significant overall CR (OR: 2.18, 95% CI: 1.80-2.63, p < 0.00001, heterogeneity: p < 0.00001, I² = 69%), and a significant acute CR (OR: 2.28, 95% CI: 1.45-3.58, p < 0.00001, heterogeneity: p = 0.04, I² = 51%). The meta-analysis revealed that the With OLN group could significantly increase the risk of dry mouth compared to the Without OLN group (OR  =  2.60, 95% CI: 1.73-3.91). In terms of insomnia, the odds ratio for the With OLN group was significantly lower than that for the Without OLN group (OR = 0.60; 95% CI 0.41-0.89). Conclusions: The results of this meta-analysis provide robust evidence that adding olanzapine to standard triple therapy significantly improves the prevention of platinum-based delayed-phase CINV, a setting where current antiemetic regimens often prove suboptimal. However, it also increases the risk of certain adverse events, especially dry mouth. Clinical decisions should be made based on a thorough assessment of the therapeutic benefits and safety risks.

(1) Background: All-trans retinoic acid (ATRA) has transformed the treatment of acute promyelocytic leukemia (APL) by inducing terminal myeloid differentiation. However, its efficacy in non-APL acute myeloid leukemia (AML) is limited. Exploring combination strategies that enhance ATRA-induced differentiation may broaden its therapeutic potential. (2) Methods: A literature search of PubMed using the keywords "ATRA," "myeloid," and "differentiation inducer or enhancer" identified more than 500 published papers as of November 2025. Pre-clinical and clinical studies were reviewed, with a focus on mechanisms, combination partners, and translational relevance. (3) Results: Clinical evidence confirms that ATRA combined with arsenic trioxide or epigenetic modulators achieves high remission rates in APL and selected AML subtypes. Pre-clinical studies show synergistic differentiation effects when ATRA is combined with CDK and kinase inhibitors, nucleotide synthesis inhibitors, DNA-damaging agents, Bcl-2/MDM2 inhibitors, proteasome inhibitors, cytokines, glycosylation modifiers, natural products, and antibiotic-derived compounds. Mechanistically, these combinations modulate key signaling pathways (MAPK, Akt, JAK/STAT), stabilize RARα, remodel chromatin, and perturb nucleotide metabolism. Although translation to non-APL AML remains limited, these findings provide a rational basis for future clinical trials. (4) ATRA-based combination therapies represent a promising strategy to extend differentiation therapy beyond APL. This review, authored solely by the investigator, highlights molecular targets and potential enhancers warranting further clinical evaluation in AML.