The ubiquitin signaling cascade plays a pivotal role in multiple cancer types, yet its role in melanoma progression remains incompletely elucidated. An unbiased and systematic analysis indicates that Ubiquitin-specific peptidase 10 (USP10), a member of USP gene family, was top priority prognostic signature for primary and metastatic melanoma progression-free survival and silencing USP10 markedly impairs the growth and metastatic potential of melanoma cells. We further uncover Forkhead box M1 (FOXM1) as a novel substrate of USP10. USP10 directly binds to FOXM1 and removes ubiquitin chains, thereby enhancing FOXM1 protein stability and driving melanoma progression. Notably, the lysine acetyltransferase KAT5 acetylates FOXM1 at residues K422 and K440, which strengthens the interaction between FOXM1 and USP10, facilitating deubiquitination and subsequent stabilization of FOXM1. Additionally, loss of either USP10 or FOXM1 suppresses the expression of the downstream target Telomerase reverse transcriptase (TERT), triggering cellular senescence. Importantly, we identify Golvatinib, as a novel inhibitor of USP10 that effectively curbs melanoma malignancy in both cellular and animal models. Taken together, these findings highlight the pro-tumorigenic role of USP10 in melanoma and suggest that disrupting the USP10/FOXM1 signaling axis could represent a viable therapeutic approach for treating this aggressive cancer.

Cancer treatments threaten fertility in reproductive-age patients. Although fertility preservation (FP) is an effective option, its communication and decision support remain inconsistently implemented in clinical practice.

To identify factors influencing FP communication and decision support from the perspective of healthcare professionals (HCPs).

A qualitative evidence synthesis of qualitative and mixed-methods studies from six databases was conducted. Influencing factors were mapped using the Consolidated Framework for Implementation Research (CFIR). Study quality was appraised using the Joanna Briggs Institute (JBI) critical appraisal checklist for qualitative research and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting standards, and the confidence in the evidence was graded using the Confidence in the Qualitative Evidence (ConQual) scale.

Factors influencing FP communication and decision support were identified across three CFIR domains. Outer setting: local fertility attitudes, geographic barriers, and policy shaped access to and engagement in FP communication and decision support. Inner setting: poor structural characteristics, survival-focused culture, limited FP knowledge, weak relational connections, and suboptimal multi-level communication hindered effective implementation. Individual: family support facilitated engagement, whereas patients' capacity and emotional state influenced their participation. Four constructs landed at a moderate confidence level, and six constructs landed at a low confidence level.

Effective FP communication and decision support require multi-level, tailored strategies targeting domain-specific barriers and facilitators.

https://www.crd.york.ac.uk/PROSPERO/view/, identifier CRD42024600847.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, largely owing to profound therapeutic resistance driven by tumor heterogeneity, a highly immunosuppressive tumor microenvironment (TME), dense desmoplastic stroma, immune exclusion, and impaired antitumor immune surveillance. Although conventional chemotherapy provides limited clinical benefit, immune-based therapies have shown modest efficacy in unselected PDAC, highlighting the need for strategies that overcome the biological barriers underlying immune resistance. Recent advances in precision medicine and bioengineering have generated a diverse range of therapeutic platforms aimed at remodeling the PDAC ecosystem. This review evaluates oncolytic virotherapy, gene-editing technologies, engineered immune-cell therapies, nanotechnology-enabled delivery systems, and artificial intelligence (AI)-assisted precision oncology according to the PDAC barriers they are intended to address and the maturity of the supporting evidence. Oncolytic viruses may enhance tumor immunogenicity and reshape suppressive immune niches, whereas gene editing and engineered cellular therapies provide opportunities to target oncogenic vulnerabilities, improve immune-cell function, and overcome antigenic and stromal constraints. Nanotechnology-based platforms can modify tissue access, payload exposure, and local immune modulation in selected models, whereas AI approaches support molecular and spatial stratification and generate treatment-prioritization hypotheses. Most supporting evidence remains preclinical or early phase, and no platform class has established broad comparative clinical benefit in unselected PDAC. Translation remains constrained by intratumoral heterogeneity, delivery limitations, safety, manufacturing complexity, and insufficient predictive biomarkers. Translation will depend on biomarker-defined enrollment and on linking administered dose to tumor exposure, target engagement, biological activity, safety, and the added benefit of the investigational component. We therefore present a barrier-matched development framework rather than a validated treatment-assignment algorithm.

Women living with HIV experience a disproportionate burden of persistent high-risk human papillomavirus infection and cervical cancer, yet they remain underrepresented in pivotal immunotherapy trials. Consequently, the effects of HIV-associated immune remodeling on the cervical cancer tumor immune microenvironment, biomarker interpretation, and response to immune checkpoint inhibition remain poorly defined. In this Review, we synthesize evidence concerning chronic inflammation, T-cell dysfunction and exhaustion, impaired antigen presentation, myeloid-mediated immunosuppression, and mucosal and microbial disruption in cervical cancer among women living with HIV. Because direct evidence in this population remains limited, we distinguish findings derived from HIV-associated cervical cancer from supporting evidence obtained in other HIV-associated malignancies, HIV-negative cervical cancer, and broader studies of HIV, HPV, and mucosal immunology. We propose a provisional inflamed, exhausted, and mucosally disrupted (IEM) framework to organize these interacting immune processes and generate hypotheses for prospective validation. This framework highlights why conventional biomarkers, including PD-L1 expression and peripheral CD4 T-cell counts, may incompletely capture immunotherapy-relevant immune heterogeneity and supports the evaluation of multidimensional biomarkers. We further discuss how the proposed framework could inform mechanism-matched therapeutic hypotheses and a novel two-dimensional clinical trial stratification model, while explicitly emphasizing that IEM is not yet a validated clinical phenotype or routine treatment-selection tool. Prospective studies incorporating women living with HIV are required to determine whether these immune features predict immunotherapy efficacy or toxicity and to establish more inclusive, biologically informed clinical-trial strategies.

Osteosarcoma is the most common primary malignant bone tumor of children and adolescents. Multiagent neoadjuvant chemotherapy once improved survival substantially, but outcomes have since plateaued. Delivering immunotherapy before surgery is attractive because the primary tumor, the tumor immune microenvironment (TIME), and the tumor-draining lymph nodes (TDLNs) remain intact. This setting may allow the TIME to be reconfigured while antigen sampling and T-cell priming are still possible. It does not, however, make the tumor a vaccine, nor does it imply that expanded tumor-infiltrating lymphocytes are tumor specific. Any benefit is instead likely to depend on antigen quality, human leukocyte antigen (HLA)-mediated presentation, the availability of tumor-reactive T-cell clones, and the reversibility of local immunosuppression. Translation remains constrained by a low but heterogeneous mutational burden, a myeloid-dominated microenvironment, and the absence of validated selection biomarkers. Preoperative treatment must also preserve its established non-immunological goals, namely downstaging to enable limb salvage and control of micrometastatic disease. We therefore examine the biological rationale, the current evidence, and the surgical, radiological, and pathological barriers to translation. We additionally consider how structural genomic instability constrains antigen availability and presentation, and how natural killer cell-directed strategies may inform barrier-matched design. On this basis we propose a barrier-matched development framework in which pathological response, spatial multi-omics, and molecular clearance jointly define success.

High Pan-Immune-Inflammation Value (PIV) has been associated with poorer survival outcomes in men with metastatic prostate cancer. However, whether PIV is associated with adverse pathology and long-term oncological outcomes in localized prostate cancer treated with radical prostatectomy (RP) remains unclear.

We retrospectively evaluated 808 men who underwent RP for prostate adenocarcinoma at Kaohsiung Medical University Hospital between 2012 and 2023; 442 met the eligibility criteria and were included in the final analysis. PIV was dichotomized using a Youden-derived cutpoint (153) based on subsequent androgen deprivation therapy (ADT), defined as any adjuvant or salvage ADT administered after RP. We used multivariable logistic and Cox regression models to evaluate associations between preoperative PIV and adverse pathological features, subsequent ADT, biochemical recurrence (BCR), metastasis-free survival (MFS), and overall survival (OS).

Median follow-up was 65.8 months. During follow-up, 100 men (22.6%) received subsequent ADT, 71 (16.1%) developed metastasis or died, and 54 (12.2%) died. High PIV was independently associated with ≥pT3 disease (adjusted odds ratio [aOR] 1.79, 95% confidence interval [CI] 1.14-2.81; p = 0.012), subsequent ADT (adjusted hazard ratio [aHR] 2.18, 95% CI 1.32-3.60; p = 0.002), shorter MFS (aHR 2.37, 95% CI 1.29-4.35; p = 0.006), and shorter OS (aHR 3.12, 95% CI 1.46-6.67; p = 0.003), but not with BCR.

High preoperative PIV was independently associated with ≥pT3 disease, subsequent ADT, shorter MFS, and shorter OS after RP, but not with BCR. These findings suggest that PIV may reflect disease progression beyond PSA-defined recurrence and may serve as a complementary preoperative biomarker. Further validation in independent cohorts is required.

Immunotherapy has improved outcomes for patients with esophageal squamous cell carcinoma (ESCC), yet a substantial proportion develop resistance. The tumor microenvironment (TME) drives this resistance through four hallmarks: physical barriers formed by cancer-associated fibroblast (CAF)-deposited extracellular matrix (ECM) and elevated interstitial fluid pressure (IFP), enrichment of immunosuppressive cells, effector T cell exhaustion, and impaired antigen presentation. Radiotherapy, a cornerstone of ESCC treatment, has the potential to simultaneously target these barriers through multiple complementary mechanisms. Preclinical evidence suggests that high-dose or ablative radiotherapy can drive CAFs into irreversible senescence, triggering a senescence-associated secretory phenotype (SASP) that upregulates matrix metalloproteinases (MMPs) and degrades ECM. In preclinical models, IFP can be reduced through vascular normalization (low-dose) or tumor debulking (high-dose). There is also evidence, largely from experimental systems, that radiotherapy may eliminate immunosuppressive cells, ameliorate T cell exhaustion, and upregulate MHC class I and PD-L1 expression to restore immune recognition. These immunomodulatory effects appear to be dose- and fractionation-dependent; conventional fractionation often falls below the threshold required to dismantle the physical barrier-a factor that is hypothesized to contribute to, but does not fully account for, the limited success of chemo-immuno-radiotherapy trials to date. Building on this mechanistic framework, we evaluate clinical evidence for radiotherapy-immunotherapy combinations in ICI-resistant ESCC, compare the distinct roles of stereotactic body radiotherapy (SBRT) and low-dose radiotherapy (LDRT), and propose a "barrier-exhaustion score" as a hypothetical tool to guide individualized treatment. This review provides a mechanistic rationale and clinical perspective for radiotherapy-based strategies to overcome immunotherapy resistance in ESCC.

Breast cancer management still depends on early detection, risk assessment, and individualized treatment. Imaging is used throughout screening, diagnosis, treatment evaluation, and follow-up. For this reason, artificial intelligence (AI) has become an active area in breast cancer imaging, especially in mammography, ultrasound, MRI, and radiomics. These methods may help describe tumor phenotype, estimate clinical risk, and predict treatment response. In daily practice, however, similar imaging findings do not always mean the same biology. Patients with similar images may have different molecular features, immune status, exposure histories, and treatment outcomes. Imaging models alone are therefore not enough to explain the heterogeneity of breast cancer. Environmental and lifestyle exposures, metabolic status, and immune regulation may also influence tumor development and prognosis. This review discusses imaging AI as a practical starting point for biomarker discovery in breast cancer. It also considers how exposome and multi-omics data may improve the biological interpretation of imaging features, and how immune dysregulation may connect external exposure, molecular change, and imaging phenotype. Current barriers include fragmented data, limited external validation, weak interpretability, fairness concerns, and difficulty in clinical implementation. Future work should focus less on building larger models alone, and more on developing transparent and validated tools that clinicians can use for risk stratification, biopsy planning, treatment-response prediction, and precision prevention. This highlights the need to integrate imaging features with multi-omics data to better interpret tumor biology and immune status.

Integrated molecular profiling has revolutionized brain tumor classification, but its ability to explain preoperative cognitive-emotional phenotypes in glioma patients relative to traditional anatomical factors remains unclear. This study investigated whether molecular features interact with tumor location to influence neuropsychological status, and whether such effects are anatomically context-dependent.

We prospectively enrolled 101 newly diagnosed glioma patients and 52 matched healthy controls. All participants underwent comprehensive neuropsychological assessments. Using a hierarchical strategy, we first stratified patients by tumor location, then examined associations of molecular characteristics and clinical factors with cognitive-emotional measures within each anatomical subgroup. Finally, multivariable regression analyses with formal interaction terms were performed in the entire cohort to test molecular-location interactions.

No significant differences in cognitive or emotional function were observed between patients with deep insular versus superficial frontal-temporal-parietal tumors. However, within the deep insular subgroup, IDH mutation remained associated with distinct patterns of emotional and attentional function after correction for multiple comparisons. Within the superficial frontal subgroup, tumor grade and several specific molecular features showed domain-specific associations with empathy or working memory. Critically, multivariable regression confirmed significant molecular-location interactions: IDH × insular for negative affect and attentional control; grade × frontal and TERT × frontal for empathy; and 1p/19q × frontal for working memory. These findings indicate that molecular features and tumor location interact to explain neuropsychological outcomes more effectively than either factor alone.

Molecular influences on preoperative cognitive-emotional status in glioma are anatomically context-dependent. Molecular features and tumor location interact to shape neuropsychological outcomes, supporting an integrated framework that incorporates both molecular and anatomical information into preoperative evaluation and personalized management strategies.

Antinuclear antibodies (ANA) are detected in cancer patients before ICI therapy, but their association with immune-related adverse events (irAEs) and outcomes is uncertain. This study aimed to characterize irAEs and tolerability in ANA-positive patients receiving ICI ± chemotherapy, and explore implications for resistance.

We retrospectively analyzed 121 solid tumor patients who received ICI therapy ± chemotherapy at the China-Japan Union Hospital (2021-2026). By baseline ANA titer (≥1:80 positive), patients were divided into positive (n=60) and negative (n=61) groups. We compared the incidence, severity, onset time, organ distribution, glucocorticoid use, and immunotherapy outcomes of irAEs between the two groups.

The incidence of irAEs was significantly higher in the ANA-positive group than in the ANA-negative group (70.0% vs. 49.2%, OR = 2.41, 95% CI: 1.14-5.09, P = 0.026). A significant dose-response relationship was observed between ANA titer and irAE risk (P_trend = 0.036), and each increase in titer category was associated with an 80% increase in risk (OR = 1.80). Autoantibody burden associated positively with irAE incidence (0 positive: 54.84%; 1 positive: 72.73%; ≥2 positive: 83.33%), although irAE severity did not increase with antibody burden (P = 0.581). The ANA positive group showed a trend toward higher irAE rates across multiple organ systems, including endocrine, pulmonary, and hepatic toxicities. There was no significant difference in the proportion of patients who discontinued ICIs because of irAEs between the two groups (20.0% vs. 21.3%, P = 1.000), and glucocorticoid use was also similar (33.3% vs. 23.3%, P = 0.357). Notably, the ANA-positive group showed a lower proportion of discontinuation due to disease progression (21.6% vs. 34.4%, P = 0.157), suggesting a potential link to delayed chemoresistance.

Baseline ANA positivity may be a potential predictor of irAE development after ICI therapy with or without chemotherapy and shows a clear dose effect relationship. ANA-positive patients exhibited a clinical pattern characterized by a high frequency but manageable irAEs; under standardized management, this did not compromise treatment continuity and may indicate stronger antitumor immune activation with potential survival benefit,potentially delaying acquired resistance to ICIs. Baseline autoantibody testing may help identify high-risk patients and guide resistance-overcoming monitoring strategies.