Skin cancer has become a global public health issue. Dermoscopy is a routine diagnostic method; however, to improve accuracy, it is often combined with skin punch biopsy and stained histological slides for microscopic observation. The manual segmentation of the lesion area by doctors involves issues such as high subjectivity and time consumption. Deep learning techniques have become a mainstream solution. Compared to foreground-background segmentation in dermoscopic images, the semantic segmentation task for whole-slide skin cancer images is more complex, requiring precise differentiation of 10 distinct tissue classes (such as tumor, epidermis, dermis, hair follicle, sweat gland, fat, etc.). Among these, various epithelial and dermal tissue types exhibit similar morphological features and are interwoven, which increases segmentation difficulty. To address this, we propose a multi-frequency domain attention-based dual encoder network (MSF-VMDNet), which combines U-Net and Vision Mamba dual encoders for parallel feature extraction. The U-Net encoder incorporates an improved AFNO spectral decomposition module, which uses a frequency domain mechanism to extract high-resolution multi-class semantic information. It further strengthens spatial information through multi-scale feature aggregation, improving segmentation accuracy at class boundaries and making the contours clearer. The Vision Mamba encoder, based on a Linear State Space Model (SSM), optimizes long-range dependency modeling and enhances both global and local feature perception. By utilizing a multi-frequency domain mechanism, this encoder maps subtle class-discriminative features from the skin histological slide into the frequency domain, reinforcing contextual features and reducing misclassification rates. In the decoding phase, the SCConv module fuses features from different frequency domains and spatial levels. Experimental results show that MSF-VMDNet significantly outperforms existing methods in terms of class segmentation performance on skin cancer histological slide datasets, achieving an MIoU of 95.37% and a Dice coefficient of 95.11%. Additionally, the model demonstrates its generalization ability in extended experiments on the ISIC 2018 dermoscopic image, PanNuke pathological cell nucleus image, and Synapse image datasets.

Purpose: We explored the association between metastatic cancer, chemotherapy, and the risk for suicide attempts (suicide injuries) in adult trauma patients.Methods: We conducted a retrospective analysis of the Trauma Quality Program Participant Use File (2017-2019), comprising 27,474 patients from 700 U.S. Trauma Centers. Self-harm/suicide injury (compared to controls) was the dependent variable; presence of metastatic cancer and current chemotherapy were the key independent variables. We adjusted for age, sex, race/ethnicity, method of payment, facility levels, and discharge year (Model 1), and Model 1 plus trauma type, injury location, stay length, comorbidities, Injury Severity Score, and Glasgow Coma Scale (Model 2). We employed chi-square analysis, Fisher's exact test, and unadjusted and adjusted logistic regression using Stata v18, setting statistical significance at P≤0.05.Results: Of 27,474 patients, 249 (0.91%) reported suicide injuries. Significantly higher attempts were noted among patients with metastatic cancer (201 out of 249; 80.72%) and those not receiving chemotherapy (184 out of 249; 73.90%), P<0.001. Metastatic cancer was associated with higher odds of suicide injuries (unadjusted OR:2.252, 95%CI: 1.642-3.089; adjusted OR in Model 1:1.925, 95%CI:1.302-2.848). Chemotherapy was associated with lower odds of suicide injuries (unadjusted OR:0.408, 95%CI:0.307-0.541; adjusted OR in Model 1:0.444, 95%CI:0.311-0.636). However, neither metastatic cancer nor chemotherapy was significantly associated with suicide injuries in adjusted Model 2, suggesting the crucial role of other factors in influencing this risk.Conclusion: Patients with metastatic cancer exhibited notable prevalence of suicide injuries. Findings suggested metastatic cancer was associated with higher odds, and chemotherapy with lower odds, of suicide injuries. Multifaceted factors were associated with suicide risk beyond the presence of metastatic cancer or chemotherapy status, underscoring the importance of mental health assessments and interventions in oncology care, particularly for those with advanced cancer.

Although immune checkpoint inhibitors (ICIs) and targeted therapies (TTs) have transformed the treatment of non-small cell lung cancer (NSCLC) across disease stages, real-world access remains highly unequal worldwide. Persistent cost barriers, fragmented reimbursement frameworks, and heterogeneous regulatory pathways limit equitable availability. The rapid proliferation of me-too agents has been proposed to counter monopolies; yet, this expansion has not consistently improved affordability. Heterogeneous evidentiary requirements-along with differences in clinical end points, comparator selection, crossover policies, and treatment duration-fragment therapeutic markets and complicate assessment of incremental clinical benefit. Divergent regulatory decisions, particularly between the US Food and Drug Administration and European Medicines Agency, underscore how trial design and geographic representation influence drug availability, especially when approvals rely on single-country data sets. These challenges are amplified in perioperative treatment strategies and rare oncogene-defined subgroups, where feasibility constraints and limited clinical equipoise hinder large randomized trials. As a result, an increasingly crowded therapeutic landscape makes cross-trial comparisons difficult and allows disparities in patient access to persist despite multiple approved therapies. Dose selection has historically followed maximum tolerated dose principles, even when preclinical and pharmacologic data suggest activity plateaus at lower exposure of ICI and TT. Dose and schedule optimization-through reduced dosing, extended intervals, or other deintensified strategies-therefore represents a rational and ethically grounded approach with a meaningful clinical impact. Such strategies may preserve efficacy while improving tolerability, reducing treatment burden, and mitigating financial toxicity, particularly in resource-limited settings. Aligning regulatory frameworks with dose optimization could promote more scalable, equitable, and sustainable NSCLC innovation.

Immune checkpoint inhibitors (ICIs) can essentially treat cancer but only in a small subset of patients. Treatment strategies capable of effectively and robustly sensitizing refractory patients to ICIs represent a highly coveted yet unmet clinical need. In this study, we identified DJ-1 as a negative T cell regulator. DJ-1 knockout boosts antitumor immunity and significantly potentiates PD-1 and TIM-3 blockades in murine cancer models. Single-cell sequencing of tumor-infiltrating CD45+ cells revealed that DJ-1 deficiency indirectly activates T cells by reprogramming macrophages. Mechanistically, loss of DJ-1 increases reactive oxygen species (ROS) in macrophages, activating NF-κB/STAT3 signaling to promote differentiation into Cxcl9+ immune-stimulatory phenotypes while reducing immune-suppressive Spp1+ macrophages. Notably, this reprogramming may be stable across tumor microenvironments because the transplanted DJ-1-deficient macrophages maintain T cell-activating capacity. Pharmacological inhibition of DJ-1 by disulfiram markedly potentiated antitumor efficacy of PD-1 blockade. This designates DJ-1 as a promising target for overcoming immune checkpoint resistance and optimize combination therapies.

Metabolic reprogramming is a hallmark of cancer, while tricarboxylic acid cycle is increasingly recognized as a multifaceted hub driving tumor metabolism and progression. Integrated analysis of solute carrier (SLC) transporters revealed consistent down-regulation of SLC13A2 in hepatocellular carcinoma (HCC) cells and liver tissues from human patients and mouse models. Adeno-associated virus-mediated liver-specific knockout or overexpression of SLC13A2 (SLC13A2-OE) promoted or ameliorated HCC progression, indicating its protective role. SLC13A2 inhibited HCC proliferation by decreasing mitochondrial function via suppressed glycolysis, respiration, and adenosine 5'-triphosphate production. Flux analysis showed that SLC13A2 imported citrate to generate acetyl-coenzyme A for pyruvate kinase isozyme type M2 acetylation, triggering its degradation. Reduced pyruvate kinase activity limited pyruvate supply, impairing amino acid synthesis and nucleotide metabolism. Moreover, SLC13A2-imported citrate induced intracellular protein acetylation, particularly histone proteins, which provided an epigenetic basis for transcriptional regulation and contributed to tumor suppression. Thus, SLC13A2 perturbs metabolic and transcriptional programs to suppress tumor growth, highlighting potential drug targets for HCC therapy.

In this article, we propose a deep reinforcement learning based chemotherapy regulation framework to realize personalized and dynamic optimization of cancer treatment. We use a nonlinear dynamic system to model the dynamic evolution of the tumor microenvironment including tumor cell, normal cell and immune cell interactions, with drug concentration serving as the control input variable. The Deep Deterministic Policy Gradient (DDPG) algorithm makes agents can study optimal dosing strategy in a continuous space of movement to inhibit tumor growth effectively and minimize damage to normal tissues. To make the strategy more stable, Gauss noise is added to the model to simulate physiological oscillations and uncertainties in the treatment reaction. Experimental results show that it can control the growth of tumor in various initial scenarios and the accumulation of the drug concentration with high flexibility and safety. Our technique provides a feasible technical way for precision, low toxicity adaptive chemotherapy.

Tumor-derived exosomes play critical roles in pancreatic ductal adenocarcinoma (PDAC) progression by mediating intercellular communication within the tumor microenvironment. This study identifies the long non-coding RNA PLBD1-AS1 as a functional oncogenic lncRNA enriched in PDAC exosomes. We demonstrate that PLBD1-AS1 promotes tumor cell proliferation, migration, and invasion by interacting with the glycolytic enzyme ALDOA and enhancing glycolytic flux. Furthermore, tumor exosomes deliver PLBD1-AS1 to pancreatic stellate cells (PSC), augmenting their glycolysis and facilitating their activation into cancer-associated fibroblasts, thereby shaping a pro-tumorigenic microenvironment. To target it, we developed an engineered exosome system modified with the tumor-penetrating peptide iRGD for specific delivery of siPLBD1-AS1 to both tumor and stromal cells. The resulting iRGD-exo-siPLBD1-AS1 construct demonstrated enhanced cellular uptake and effectively suppressed PLBD1-AS1 expression, inhibited glycolysis, impaired PSC activation, and significantly attenuated tumor growth. Our findings reveal a novel mechanism of exosome-mediated metabolic crosstalk in PDAC and establish a promising RNAi-based therapeutic strategy targeting this lethal malignancy.

Despite the availability of several chemotherapeutic regimens for early-stage breast cancer (BC), the ideal combination and dosing strategy remain to be defined. Thus, we conducted a network meta-analysis (NMA) comparing the current chemotherapeutic regimens used in the treatment of women with early-stage BC.

Progastrin, is over-expressed in human colorectal tumor cells and also directly targets the ß-catenin/Tcf4 oncogenic pathway, The association between Wnt/ß-catenin pathway and cancer is not merely restricted to colorectal cancer as disruption of this pathway results in epithelial mesenchymal transition in oral carcinogenesis. As therole of progastrin in subjects with Oral cancer(OC) is less explored, this study was contemplated to assess the role of plasma progastrin levels in subjects with various stages of oral squamous cell carcinoma.

In Algeria, breast cancer accounts for 37.8% of new cancer cases in women. It is an epithelial cell tumor in most cases. CA15-3 (carbohydrate antigen) is the marker of choice for therapeutic monitoring, although ASCO (the American Society of Clinical Oncology) does not recommend its routine use, preferring CYFRA21.1 (cytokeratin19 fragment) to assess response to treatment. The aim of this study was to estimate the degree of correlation between these two biological markers as a function of tumour histological type and the presence or absence of metastases. In a prospective descriptive study, sera from 110 breast cancer patients (mean age 49 ± 7.23 years) were measured using the electrochemiluminescence (ECL) technique to assess CYFRA 21.1 and CA 15.3 levels. Comparison of CA15.3 and CYFRA21.1 levels between patients and controls (79 controls) showed a highly significant association (p<0.0001) between these two markers and breast cancer. The significant correlation between CA15.3 and CYFRA21.1 (r=0.245; P< 0.0001) suggests that reliance on CYF 21.1 for monitoring breast cancer patients undergoing chemotherapy is possible. The results show a good correlation between the two markers, especially for the two histological types luminal a and luminal b+HER2 (r=0.602 ; p<0.0001, r=0.505 ;p< 0.0001 respectively). This study also assessed the correlation between CA15.3 and CYFRA21.1 levels in patients with and without metastases. A significant correlation was also found between CA15.3 and CYFRA 21.1 in the presence of metastases (r=0.472, p<0.0001). A multi-marker approach could provide a more comprehensive assessment of tumor burden and response to treatment.

Accurately estimating physiological fitness and life expectancy is challenging in older patients with early-stage non-small cell lung cancer (NSCLC) considered for stereotactic body radiotherapy (SBRT). Noninvasive biological age metrics may improve assessment beyond chronological age.

Real-world evidence (RWE) is increasingly used in health technology assessment (HTA) to address uncertainties surrounding the generalizability of randomized clinical trial (RCT) data. Pembrolizumab plus platinum-based chemotherapy improves survival in metastatic, non-small cell cancer (mNSCLC); however, existing economic evaluations primarily rely on RCT inputs. This study aimed to provide a within-model comparison of cost-effectiveness estimates derived from RCT and population-based RWE for pembrolizumab plus platinum therapy versus platinum therapy alone.

IntroductionThe prognosis differences of gastrointestinal stromal tumors (GISTs) between the jejunum and ileum have rarely been studied. This study aimed to evaluate the long-term survival outcomes in patients with jejunal and ileal GISTs.MethodsThis population-based retrospective cohort study utilized data from the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2019. Kaplan-Meier analyses and Cox proportional hazards models were employed to assess overall survival (OS) and cancer-specific survival (CSS). A 1:1 propensity score matching (PSM) approach was implemented to address confounding factors, and subgroup analyses were performed for various variables.ResultsA total of 1237 patients were analyzed, with 848 in the jejunum and 389 in the ileum. Ileal GISTs patients were older, exhibited higher T stages, larger tumor sizes, elevated mitotic rates, and were more susceptible to distant metastasis (P<0.05). After PSM, the jejunal GISTs group and the ileal GISTs group demonstrated comparable OS (hazard ratio [HR]: 1.25, 95% confidence interval [CI]: 0.97-1.60, P=0.082) and CSS (HR: 1.13, 95% CI: 0.81-1.59, P=0.461). Additionally, jejunal GISTs and ileal GISTs exhibited similar OS and CSS across various subgroups. Multivariate Cox regression analysis revealed age, TNM stage, and mitotic rate as independent risk factors influencing OS, whereas race, N stage, and M stage were identified as independent risk factors affecting CSS.ConclusionsJejunal GISTs and ileal GISTs have comparable OS and CSS, with the occurrence of lymph node metastasis and distant metastasis being important factors affecting their prognosis.

Diabetes mellitus and cancer are growing global health concerns with a rising prevalence and substantial associated mortality. The study aims to find impact of diabetes mellitus in cancer. A narrative review was conducted by analysing evidence from various sources, including meta-analyses, systematic reviews, retrospective studies, database analyses, and cohort studies. The review explored the complex interplay between Diabetes Mellitus and cancer, like cancer incidence, oncology outcome i.e., acute and late toxicities, treatment compliance, overall survival (OS), and quality of life (QoL). Diabetes mellitus increases the risk of developing cancer by 10%. Diabetic patients had higher infection rates [2.6%-52%, odds ratio (OR) 1.38-1.57], increased haematologic toxicity (13%-65.7%, P=0.004), and greater hospital admissions (17.2%-74.5%, OR 2.1, P< 0.001). They received significantly lower cisplatin doses (18%-33% reduction), experienced more surgical delays [adjusted OR 1.16, 95% confidence interval (CI) 1.05-1.27], higher risk of flap failure (RR=1.83, 95% CI 1.18-2.85, P=0.007) and were less likely to undergo breast reconstruction (adjusted OR 0.48-0.54, 95% CI 0.24-1.00). Diabetes mellitus decreases local control by 10-20%, increases mortality by 27-98%, and decreases OS by 18-50% across various cancers. It increases late toxicity and negatively impacts QOL with a 1.3-2.7 times higher risk of grade ≥2 genitourinary and gastrointestinal toxicity in prostate cancer, a twofold increase in grade ≥3 radiation pneumonitis in lung cancer, and a 50% higher incidence of severe peripheral neuropathy in breast cancer, leading to delayed recovery and long-term morbidity. In patients receiving cancer directed therapy, diabetes mellitus increases acute and late toxicities, decreased local control and overall survival, and have poor quality of life.

Background and objectives The relationship between sarcopenia and prognosis in patients undergoing chemotherapy for testicular germ cell tumours remains underexplored. We aimed to evaluate the impact of sarcopenia on disease progression and overall survival in these patients. Methods This retrospective multicentre study included patients who received chemotherapy for testicular germ cell tumours between January 2010 and December 2023. The psoas muscle index was calculated by measuring the cross-sectional area of the psoas muscle at the third lumbar vertebral level and was divided by the square of the height. Patients were divided into two groups based on changes in PMI (before and after chemotherapy): Group 1 (<10% change) and Group 2 (≥10% change). Results A total of 159 patients were analysed. Of these, 113 (71.1%) were in Group 1 and 46 (28.9%) in Group 2. Group 2 showed higher rates of disease progression (26.1% vs. 10.6%) and mortality (8.7% vs. 1.8%) (P=0.023 and P=0.038, respectively). In multivariable analysis, ≥10 % decrease in psoas muscle index [Hazard Ratio (HR)=6.499, P<0.001], rete testis invasion (HR=3.459, P=0.007), and non-seminomatous/mixed histology (HR=5.777, P=0.020) were identified as independent predictors of disease progression. For mortality, only a ≥10 % decrease in psoas muscle index was found to be a significant predictor (HR=5.994, P=0.049). Interpretation and conclusions A reduction in PMI is an independent prognostic factor for both disease progression and mortality in patients undergoing systemic chemotherapy for testicular germ cell tumours.

Telomerase is active in the majority of high-risk neuroblastomas, a pediatric tumor associated with poor patient outcomes. In other cancer types, resistance to immune checkpoint blockade was overcome by induction of telomere dysfunction using the telomerase substrate precursor 6-thio-2'-deoxyguanosine (6-thio-dG). Here, we explored whether induction of telomere dysfunction improves the anti-tumor efficacy of immune checkpoint inhibition in neuroblastoma. 6-thio-dG treatment induced the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway and programmed cell death ligand-1 (PD-L1) expression in murine neuroblastoma cells in vitro. In a MYCN;ALKF1174L-driven transgenic neuroblastoma mouse model, 6-thio-dG treatment delayed tumor growth and prolonged survival. Treatment with anti-PD-L1 also led to growth delay and improved survival, which occurred; however, only after an initial lag phase. Combination with anti-PD-L1 improved the anti-tumor effects of 6-thio-dG and overcame the initial lag phase of anti-PD-L1 treatment. Mechanistically, 6-thio-dG combined with anti-PD-L1 treatment induced cGAS and PD-L1 expression and promoted immune cell infiltration in the tumors. Our findings suggest that 6-thio-dG treatment activates the cGAS-STING pathway in neuroblastoma and that induction of telomere dysfunction in combination with immune checkpoint blockade boosts intratumoral immune cell infiltration and improves survival in a high-risk neuroblastoma mouse model.

Supernumerary centrosomes are a hallmark of cancer. To maintain viability, cancer cells cluster these centrosomes during mitosis, enabling bipolar division similar to that of normal cells. Disruption of this centrosome clustering leads to multipolar anaphase and apoptosis (anaphase catastrophe), which selectively eliminates cancer cells harboring supernumerary centrosomes. In this context, because the motor protein KIFC1 contributes to centrosome clustering, we investigated whether targeting of this mechanism through KIFC1 inhibition could be exploited in small-cell lung cancer (SCLC), an aggressive malignancy with limited treatment options and poor prognosis. Through in silico and in vitro analyses, as well as IHC of clinical samples, we found that KIFC1 is overexpressed and that centrosome amplification occurs more frequently in SCLC compared with normal tissues and other cancer types. Pharmacological and genetic inhibition of KIFC1 disrupted the clustering of supernumerary centrosomes, triggered multipolar mitosis, and exerted antineoplastic effects in SCLC cells, with minimal effects on noncancerous cells. These findings were validated and extended in vivo using SCLC xenograft models. Finally, cotargeting KIFC1 and the centrosome duplication regulator PLK4 further enhanced growth suppression in SCLC cells. Together, these results suggest that disrupting centrosome clustering and triggering anaphase catastrophe via KIFC1 inhibition may represent a promising therapeutic strategy for SCLC.

Neuropilin-1 (NRP1) is overexpressed in various malignant solid tumors, modulating the tumor microenvironment (TME) via multiple mechanisms to promote immune suppression, angiogenesis, and epithelial-mesenchymal transition (EMT), ultimately resulting in poor patient survival. Autophagy, a highly conserved cellular self-degradation process, plays a stage-dependent, bidirectional role in cancer. At early stages it suppresses tumorigenesis by clearing damaged cellular components, whereas at advanced stages it supports tumor survival under stress and thereby enhances proliferation, invasiveness, and therapy resistance. The interplay between NRP1 and autophagy in the TME is characterized by reciprocal regulation: NRP1 activates certain pathways to regulate autophagy, whereas autophagy induction promotes NRP1 degradation. This bidirectional interplay directly governs tumor progression and therapy resistance. Although prior studies have provided some clues about their interaction, the regulatory network and the precise mechanisms linking NRP1 and autophagy in the TME remain incompletely characterized. Precision therapies targeting the NRP1-autophagy axis still face multiple obstacles. This review synthesizes data from the atlas cancer genome (TCGA), the genotype-tissue expression (GTEx) database, and the human autophagy database (HADb) to explore associations between NRP1 and autophagy-related gene (ATG) in expression and prognosis, elucidate NRP1-autophagy interaction mechanisms and therapeutic opportunities and challenges in targeting the NRP1-autophagy axis. Pan-cancer analysis showed significant upregulation of NRP1 in 10 solid tumor types and revealed co-expression relationships between NRP1 and 340 ATGs. Among these, co-expression patterns involving genes such as CXCR4 and HSPA5 had significant prognostic value in gastric cancer and glioblastoma. This review systematically explores the panoramic regulatory framework of the NRP1-autophagy axis in the tumor immune microenvironment through bidirectional regulation of activating immunity and inhibitory immunity at the pan-cancer level. It fills the gap in the systematic summary of the NRP1-autophagy axis in regulating the dynamics of the tumor immune microenvironment, and provides a theoretical basis for the clinical translation of combination chemotherapy and immunotherapy targeting the NRP1-autophagy axis.

Exosomes can promote tumor development and regulate tumor immune responses, making them of significant value in Lung Adenocarcinoma (LUAD) management. In-depth exploration of exosome-related genes in LUAD is of great significance for expanding LUAD clinical treatment options.

Therapeutic resistance remains the principal cause of mortality in breast cancer. While the tumor microenvironment (TME) is a key contributor, therapies targeting isolated TME components, whether immune, metabolic, or spatial, have largely failed due to compensatory adaptations and ecological resilience. This review synthesizes recent advances to propose a tripartite "Immune-Metabolic-Spatial" axis as the fundamental organizer of a robust resistance niche. We elucidate how immunosuppressive cells, such as TAMs and Tregs, are metabolically sustained by altered nutrient availability like lactate and hypoxia, while spatial constraints, including CAF-deposited ECM and DDR1-mediated collagen alignment, physically impede drug delivery and immune infiltration. Critically, we highlight reciprocal crosstalk where metabolic reprogramming dictates immune cell function, in turn influencing stromal remodeling to create a self-reinforcing resistance loop. Beyond mechanism, we evaluate emerging strategies that concurrently target multiple axes, such as combining immune checkpoint blockade with metabolic inhibitors or stromal disruptors. Finally, we discuss clinical translation through biomarker development and innovative trial designs, framing the tripartite axis as an actionable framework for overcoming therapeutic resistance.