Glioblastoma (GBM) frequently develops resistance to temozolomide (TMZ), limiting the effectiveness of standard therapy. Histone deacetylase (HDAC) inhibitors have emerged as potential chemosensitizers; however, the comparative performance of these inhibitors and the associated mechanistic impact remain incompletely characterized.

In vitro, this study systematically evaluated the effects of the Class I-selective HDAC inhibitors Entinostat and Tucidinostat, and the pan-HDAC inhibitor Vorinostat on TMZ sensitivity in multiple GBM cell lines (U87, U251, LN229). Additionally, this study assessed cell viability, morphology, and the expression of selected markers glial fibrillary acidic protein (GFAP), microtubule-associated protein 2 (MAP2), class III β-tubulin (TUBB3), and synapsin I (SYN1). In vivo, the therapeutic efficacy of Entinostat combined with TMZ was evaluated in a U87 xenograft mouse model by measuring tumor growth, and the expression of GFAP and TUBB3 was examined in tumor tissues. Clustered Regularly Interspaced Short Palindromic Repeats associated protein 9 (CRISPR-Cas9)-mediated knockout of HDAC1/2/3 was used to test the dependence of these effects on canonical Class I HDACs.

Entinostat and Tucidinostat significantly enhanced TMZ-induced cytotoxicity across all cell lines, demonstrating greater TMZ-sensitizing activity than Vorinostat under the conditions tested. Treatment was associated with altered cell morphology and changes in marker expression, including reduced GFAP and increased MAP2 and TUBB3. In the U87 xenograft model, Entinostat combined with TMZ significantly suppressed tumor growth and was associated with decreased GFAP and increased TUBB3 expression. Importantly, both TMZ sensitization and the associated morphological and marker changes persisted in HDAC1/2/3-knockout cells, suggesting that the effects are not fully explained by HDAC1/2/3 depletion. These effects were consistent across multiple cell lines and in xenograft tumors.

Entinostat and Tucidinostat enhance TMZ sensitivity in GBM models and are associated with specific markers and morphological changes that persist despite HDAC1/2/3 knockout. These findings support further evaluation of Entinostat and Tucidinostat as TMZ-sensitizing agents in GBM models and highlight associated phenotypic and molecular changes that warrant further mechanistic validation.

Cancer neuroscience has emerged as a field that explores the bidirectional interactions between tumors and the nervous system. From this perspective, we review the pharmacological and neurobiological effects of kinase inhibitors, which are widely used as anticancer therapeutics. Certain kinase inhibitors not only exert potent antitumor activity but also modulate neural function as a consequence of kinase inhibition. Representative examples include small molecules and therapeutic antibodies targeting the tropomyosin receptor kinase (Trk), rearranged during transfection (RET), vascular endothelial growth factor/ vascular endothelial growth factor receptor (VEGF/VEGFR), epidermal growth factor receptor (EGFR), and anaplastic lymphoma kinase (ALK) signaling pathways. These agents influence the nervous system through molecular mechanisms, examples of which include TrkA-mediated pain perception and growth differentiation factor 15/RET signaling-dependent appetite regulation. Elucidating these mechanistic intersections between oncogenic and neural signaling can broaden our understanding of tumor-nerve crosstalk.

A common cause of multidrug-resistant (MDR) cancer is imbalanced redox signaling, which reduces the effectiveness of chemotherapy and promotes regrowth of cancer cells. Amplification of thioredoxin reductase (TrxR) and activation of the Keap1-Nrf2-FOXO3 pathway may contribute to enhanced drug efflux, strengthens antioxidant defenses, and resistance to oxidative stress-induced apoptosis in certain tumors. Redox-based drug repurposing offers a promising strategy to overcome MDR by targeting these shortcomings. Repurposing drugs including metformin, auranofin, brusatol, and natural polyphenols increase reactive oxygen species (ROS) and make MDR cells more sensitive to chemotherapy via modulation and inhibiting Nrf2 or TrxR. Nanotechnology advancements and combination of repurposed drugs with anticancer drugs, ferroptosis inducers may improve tumor selectivity while lowering systemic toxicity. Preclinical experiments show effectiveness by suppressing antioxidant pathways, inhibiting efflux pump function, and delivering drugs in a redox-responsive manner. Next-generation tumor-selective delivery systems, adaptive clinical trial designs, and biomarker-driven patient classification based on TrxR expression or Keap1/Nrf2 mutations are the main areas of focus. Translation into clinical practice could be accelerated by combining specific redox profiling, nanocarrier technologies, and pharmacokinetics. For MDR cancer, redox-targeted drug repurposing is an effective, precision-based strategy for recovering chemosensitivity and enhancing treatment outcomes.

Bladder cancer is a long-standing clinical issue, with frequent recurrence and continuously disappointing results in patients, so that therapeutic development is primarily reliant on delineating the original molecular defects. Increasing interest has turned to the Kinesin Superfamily Proteins (KIFs), basic molecular motors that move along microtubule rails, and are now emerging as important key oncogenic derivers in bladder cancer pathogenesis. This review synthesizes available evidence indicating that several KIFs, specifically KIF4A, KIF14, KIF20A, and KIFC1, function as key oncogenic regulators and represent important prognostic biomarkers and therapeutic targets in bladder cancer. When KIF expression or activity is disrupted, it provides mechanical and signaling support for all the cancer hallmarks, facilitating cellular proliferation, invasion, metastasis, and resistance to highly effective cell death. Its oncogenic activity is generally facilitated by the activation of principal signaling pathways. A remarkable proportion of certain KIF isoforms are commonly overexpressed in cancer, and the scale of such overexpression increases with the severity of adverse clinical predictors, such as increasing disease stage, and patient survival worsens. This nuanced molecular image renders KIFs so highly promising targets for therapeutic intervention and prognostic stratification, and initial exploration of kinesin inhibitors is encouraging to abate chemoresistance, aside from optimizing the efficacy of current immunotherapies. Uncovering modalities that exploit the aggressive bladder cancer cell dependence on KIF motor activity is a highly promising path to clinical application.

Composite indolent B-cell lymphomas may remain unrecognized when one component dominates the clinical presentation. Apparent relapse after therapy may, therefore, represent the emergence of a biologically distinct lymphoma rather than the recurrence of the original disease.

An 82-year-old woman presented with systemic low-grade B-cell lymphoma that was most consistent with marginal zone lymphoma (MZL). Staging demonstrated peripheral blood involvement and multifocal FDG-avid disease. Treatment with the CD20×CD3-bispecific antibody mosunetuzumab resulted in complete metabolic remission. During surveillance, a new, isolated cervical lymph node developed despite sustained systemic response. Biopsy revealed follicular lymphoma (Grade 1-2) with a germinal center phenotype and a BCL2 rearrangement, findings discordant with recurrence of MZL. Retrospective review of the original specimen identified in situ follicular neoplasia within the initial biopsy. The disease course was, therefore, reinterpreted as a synchronous composite lymphoma in which treatment of the dominant MZL unmasked a previously clinically silent B-cell neoplasm with follicular lineage. Local radiotherapy achieved remission of the follicular component.

New disease following treatment of an indolent lymphoma should not automatically be interpreted as relapse. Discordant clinical behavior, particularly focal progression after systemic response, warrants repeat biopsy and integrated pathologic reassessment. This case illustrates how therapy may reveal preexisting clonal heterogeneity and emphasizes the importance of temporality in distinguishing relapse from composite lymphoma.

The authors have confirmed clinical trial registration is not needed for this submission.

Systemic pro-inflammatory cytokine therapies (e.g., IL-2) represented early milestones in immunotherapy, but their use is hampered by low response rates and severe off-target toxicity. In contrast, immunocytokines deliver cytokines directly to tumors, reducing systemic toxicity and enhancing efficacy. Spatial-omics provides deep insights into the tumor microenvironment (TME), enabling identification of druggable targets and accelerating development of novel antibody platforms and cytokine payloads. However, variability in patient sample quality affects data integrity, and platform differences require distinct preprocessing workflows. Spatio-temporal data demand spatial clustering to define disease-relevant niches, yet a lack of consensus about what constitutes a niche complicates interpretation and reproducibility. To overcome these challenges, effort needs to be made to improve sample collection and processing, and to reconcile the diversity of platforms with their technical limitations in niche identification. By combining knowledge of key TME cell types and marker expression with cytokines identified from autoimmune datasets, innovative immunocytokines can be designed to improve targeting, effectiveness, and patient outcomes.

Clear cell renal cell carcinoma (ccRCC) is a kidney cancer in which immune activity is closely intertwined with von Hippel-Lindau (VHL) loss, hypoxia-inducible factor (HIF) signaling, angiogenesis, hypoxia, and metabolic adaptation. Although immune checkpoint inhibitor (ICI)-based regimens have changed the treatment landscape of advanced ccRCC, only a subset of patients achieve durable benefit. Commonly used biomarkers, such as programmed death-ligand 1 (PD-L1) expression, tumor mutation burden (TMB), and broad inflammatory gene signatures, have not been sufficient to explain this variation or to guide routine treatment selection. One reason is that immune infiltration in ccRCC is not synonymous with effective antitumor immunity. A tumor rich in CD8+ T cells may still be resistant if these cells are exhausted, metabolically restricted, spatially separated from tumor nests, or surrounded by suppressive myeloid, stromal, and vascular programs. Therefore, the key issue is not simply whether a tumor is immunologically "hot" or "cold," but which part of the antitumor response has failed. In this Mini Review, we discuss ccRCC immunotherapy response from an immune-ecological perspective. We focus on several treatment-relevant immune states, including T-cell-inflamed but dysfunctional tumors, myeloid-dominant suppressive tumors, angiogenesis- and hypoxia-skewed tumors, and immune-excluded tumors. We also consider how bulk transcriptomics, single-cell and spatial profiling, T-cell receptor sequencing, proteomics, metabolomics, and longitudinal liquid biopsy may help define these ecotypes and capture treatment-induced remodeling. This perspective may support more refined patient stratification and more mechanism-matched immunotherapy strategies in ccRCC.

To investigate the mechanisms underlying benzo[a]pyrene-induced esophageal cancer (EC), and to screen and identify the key targets and biomarkers associated with benzo[a]pyrene-related EC.

Potential targets of benzo[a]pyrene (BaP) were predicted using PharmMapper, SwissTargetPrediction, and ChEMBL databases, and were intersected with differentially expressed genes (DEGs) from the GEO database to screen candidate key genes. Subsequently, diagnostic models were constructed using 14 machine learning algorithms based on the identified key genes. Meanwhile, a prognostic model of key genes was constructed based on the TCGA esophageal cancer cohort, and the correlation between these key genes and tumor immune infiltration was further explored. Additional explainability was provided via SHAP analysis by determining the contributions of key features. Molecular docking was performed to verify the binding between BaP and core targets.

A total of 82 genes were identified as potential targets of EC induced by BaP. These key genes were found to be mainly involved in core tumor-related pathways, cell cycle regulation, MAPK signaling, and immune-inflammatory pathways, covering the crucial biological processes underlying malignant transformation of EC. Subsequently, 12 core genes (ACOT9、ACOX3、AURKA、HMGCR、INHBA、MMP3、MSR1、SHC1、SORT1、MAOB、MMP13、CDK4) were identified as key regulators by machine learning analysis. Among them, SORT1 and ACOX3 were significantly down-regulated, while AURKA and MMP13 were markedly up-regulated (P < 0.05). The 12-gene prognostic model enables efficient prognostic stratification of esophageal cancer patients, and core genes are implicated in the remodeling of the esophageal cancer immunosuppressive microenvironment through the regulation of immune cell infiltration. Molecular docking revealed strong binding ability between BaP and target proteins.

Bioinformatics analysis and molecular docking results revealed significant associations between BaP and 12 core esophageal cancer-related genes. BaP could stably bind to core proteins including AURKA, CDK4, MMP13 and INHBA, which is potentially correlated with altered cell cycle, metabolic disorders and dysregulated tumor immune microenvironment in esophageal cancer. 12 core genes were identified via machine learning, which offers new perspectives for the interdisciplinary field of environmental toxicology and precision oncology and provides a foundation for the development of individualized therapeutic strategies.

Multiple primary lung cancer (MPLC) is an increasingly recognized subtype characterized by distinct lesions with independent origins. While recent studies have profiled the immune landscape of MPLC, its tumor-intrinsic metabolic features and immunoregulatory interactions remain largely unexplored.

Single-cell RNA sequencing data from 11 single primary lung cancer (SPLC) tumors and 8 samples from 4 MPLC patients were analyzed using dimensionality reduction, clustering, and cell type annotation. Subtype-specific metabolic features and intercellular communication patterns were investigated through pathway enrichment and cell-cell interaction analyses. A prognostic model was constructed using Lasso-Cox regression. Immune microenvironment characteristics were assessed using deconvolution algorithms and immune-related signatures. Drug sensitivity prediction and functional assays were performed to explore potential therapeutic implications.

This study identified a metabolically distinct malignant epithelial subpopulation enriched in MPLC tumors, characterized by upregulation of amino acid metabolism pathways and active MHC-II-mediated interactions with immunosuppressive CD4⁺ Treg cells and mast cells. A metabolism-based eight-gene prognostic model was developed and validated in independent lung adenocarcinoma cohorts, effectively stratifying patient survival outcomes. High-risk patients exhibited immunosuppressive tumor microenvironment features, reduced immunotherapy response potential, and distinct drug sensitivity profiles. Functional assays confirmed that key metabolic genes, spermine oxidase (SMOX) and spermine synthase (SMS), promoted tumor proliferation and invasion, accompanied by transcriptional changes in PI3K/mTOR pathway components, highlighting their potential roles in poor prognosis and therapeutic vulnerability.

This study provides a systematic characterization of malignant subpopulations in MPLC, highlighting metabolic reprogramming and immunoregulatory features that contribute to poor prognosis. These findings provide a rationale for metabolism-based prognostic stratification and highlight potential therapeutic strategies to improve clinical outcomes.

Prediction models for postoperative recurrence in papillary thyroid carcinoma (PTC) have increased substantially in recent years. However, recurrence outcomes are inconsistently defined across studies, particularly with respect to structural and biochemical recurrence, and the quality and clinical applicability of existing models remain uncertain.

To systematically review and critically appraise multivariable prediction models for structural postoperative recurrence in pathologically confirmed PTC and to evaluate their predictive performance, methodological quality, and risk of bias.

PubMed, Embase, and the Cochrane Library were searched from inception to February 2026. Studies developing or validating multivariable prediction models for structural recurrence in adult patients with PTC were included. Data extraction was guided by the CHARMS checklist, and risk of bias was assessed using PROBAST. Findings were synthesized narratively, and an exploratory meta-analysis of discrimination performance from validation studies was conducted where appropriate.

Thirteen retrospective studies met the inclusion criteria, all of which were conducted in East Asian populations. Reported discrimination was generally acceptable, with most AUC or C-index values exceeding 0.70. However, all studies were judged to have a high overall risk of bias, primarily due to limitations in the analysis domain, including inadequate handling of overfitting, insufficient sample size justification, limited reporting of missing data, and reliance on internal validation. Only two studies performed external validation. Exploratory pooling of validation AUCs suggested moderate predictive performance but substantial heterogeneity across studies.

Current prediction models for structural recurrence in PTC show promise for individualized risk estimation but remain limited by methodological weaknesses, heterogeneous modelling approaches, inadequate assessment of calibration, and scarce external validation. Future studies should adopt standardized recurrence definitions, improve reporting transparency, and prioritize robust external validation before routine clinical implementation can be recommended.